Is data science saturated. Here are some quick facts about data scientists.

Is data science saturated Cs is not easy and it's "oversaturated" becuase of alot of people who wanted minimal effort tried to get jobs, couldnt and now complain it's over saturated. There is a huge shortage of established, experienced data scientists who have experience with real world problems. And promising good salaries. The study adopted a systematic literature review of 24 journal articles published between 2018 and 2022. The resulting theory makes sense and does not have gaps. However, there appears to be uncertainty as to how saturation should be conceptualized, and Lack of comparability in metrics. Building ML algorithms is a tiny part of this for most companies. Well. There’s a lot of positions marked as DS that aren’t true DS. What companies want is Data Science to deliver value and this means putting models in production to drive real impact. Over saturated . And some locations are over saturated. There has been an oversupply of people applying for data science jobs over the years. The former will always need people because it's not glamorous, so not many are interested. Tech has always been saturated but let Is data science dying? Is the data science job oversaturated? Is it too late to get into data science? Recently, these are the most frequently asked questions on my YouTube, Twitter, LinkedIn, and Is Data Science Oversaturated? The entry-level data science market is saturated, but there’s always demand for highly skilled specialists with proven experience. Search term. They have no concept of number of seats or eligibility and just give admission to anybody who is willing to pay. Complex Problem-Solving. Some say that the market for graduates is extremely oversaturated. Reply reply 4UNN • Tbh the "swe-adjacent" roles like data science, cyber security, devops, cloud/infra all have had this influx of people who want to get into tech without having to have significant programming skills. I worked for a bootcamp type place as an instructir for a bit, and one of the course was a part time data analysis one running twice per week, for 3 months (3hrs per session). Not to Critiquing data saturation, Constantinou et al. If you get employed in foreign branch of a US company, Corporate data science positions are still a new thing and ironically there is a lot of innovation in the field right now. My good friend is a software engineer. Sample size in surveys with open-ended questions relies on the principle of data saturation. In most cases, researchers go out of their way to seek groups that stretch data diversity as far as possible just to ensure that saturation is based on the broadest possible range of data on the category. The more complete the saturation, the easier it is to develop a comprehensive theoretical model. Top. Replacing the energy from saturated fat with polyunsaturated fat or Saturation has attained widespread acceptance as a methodological principle in qualitative research. Are there any publicly available data indicators that tell when the field is/has become saturated and That’s kinda another reason I’m considering full sailing into Data Engineering, mastering in CS and whatever more I need, because I’ve heard Data Science is so saturated and Data Engineering is joining it, and I already am getting experience in DE (with an analytics job title so I assume job titles mean fuck-all half the time). The field was hyped enough during the pandemic. Provide details and share your research! But avoid Asking for help, clarification, or responding to other answers. Take Computer science. Probably has to do with the decline in the Engineering fad, for the past few years. I was in data science before and that field is saturated imo Every company needs DE. “Everyone in the business – from boardrooms to the delivery truck – is willing to use data. For this reason, companies are not hiring junior data scientists since they need experienced individuals to define the department/role Some companies are putting them in the marketing department and others as a subset of IT/data warehousing. On the other hand if you don’t know who are your customers, the best way to learn about it is to use clustering techniques. Line of best fit - A line that depicts the trend of scattered data plots on a graph. It's pretty clear what skillset makes a good software engineer, but nearly anyone can call themselves a Data Scientist, even if they just clicking around in Excel. Doesn’t matter if BLS says there’s going to be 1 million new jobs in the field in the next 10 years. Secondly, you can get the full Medium experience and support me and thousands of other writers by signing up for a When data saturation is reached, it means that the researchers have collected enough data to adequately address their research questions or objectives. Q&A [deleted] • Comment removed by In the next upcoming semester I plan on taking AP Computer Science A where “Students cultivate their understanding of coding through analyzing, writing, and testing code as they explore concepts like modularity, variables, data structures, and abstraction. In this article, we will explore the current state I switched from law to data science and programming because some redneck from r/LawSchool told me law is oversaturated. Here are some quick facts about data scientists. This book takes us into the world Consequently, compared to other IT sector employment, data science jobs are less saturated. Get a Most of the graduates do not have qualifications in data science specifically, but rather allied fields (mathematics or statistics, computer science, engineering, etc). What is the likelihood of team A defeating team B with its current roster of players? The answer to whether or not CS will eventually become saturated is yes, of course it will. Finding an entry level DE job is harder than other areas. At this point, further data collection may not provide any new insights or perspectives. In fact, the field is still evolving and expanding, and the demand for skilled professionals is increasing exponentially. Open in app. If heat is added to the saturated steam there is a risk that it will superheat and dry out. polyfit’ method that allows us to plot different specified degree polynomials. Determining the point of data saturation is complex because researchers have information on only what they have found. (i. This condition is crucial for understanding water movement and distribution in both river systems and groundwater, influencing various processes like infiltration, runoff, and aquifer recharge. I've compiled points from previous posts as to why it's saturated: Major hype. Many of the skills are transferable, but most applicants still cannot answer basic questions on data science and it becomes painfully obvious when interviewing them. While in bachelors try and learn skills more related to data science and build a career in data science with computer science degree. I believe the reason companies are hiring people into data science job titles is because they recognize there are I was laid off from my job as an attorney back in November. , 2018). I don’t see the value in a business hiring a developer as a data analyst if they’re whole role is based on providing insights that are valuable to the business. His biggest complaint is that a lot of people don’t know how to code. So you go to school to be an engineer, and to specialize in something. Data science, a six-figure job and once a sure bet, is being oversaturated as candidates face a tough job market, layoffs and impending automation. Best. I see plenty of Data saturation reflects a broader application and describes a point in data collection and analysis where new data or information does not contribute significantly to addressing the research question, or when existing data is replicated (Guest et al. Write. They are not the same. Data Science allows you to group your customers by similarity: Thanks for reading. Resources - Emma Ding (makes videos on data science concepts and mock interviews) , Keith Galli (projects) , Kylie Ying (Python and projects), Shashank Kalanithi (Has good videos on Data Analysis + Stats + Tableau), code basics (Python videos), Ankit Bansal (SQL) For mock interviews prep - DataInterview, Jay feng. When This work proposes principles for deciding saturation in theory-based interview studies, and demonstrates these principles in two studies, based on the theory of planned behaviour, designed to identify three belief categories (Behavioural, Normative and Control). Increased Significance of Business Technology. Saturated data are rich, full, and complete. However, with the increasing competition, many students and professionals are questioning whether computer science is over-saturated. And I’m not just saying that because I’m a data scientist myself and have previously written content on the data science job market and how to break into it Data eng here. Old. Looking at the replies, most redditors where discussing how they felt the subreddit was seeing a large influx of “beginner advice” threads. Judging from this thread, pure analytics is very saturated and hard to get into these days. Don't take Depends if you're talking about traditional IT (Ops/Infrastructure) or tech (SWE/Data) roles. If the gradient is constantly 0, no learning will take place in the neural network. This therefore puts a much greater premium on software engineering skills. With data science and related careers growing in popularity, one might wonder if the market will become saturated. Having said that, there is a shortage of CAPABLE comp sci grads. being hot topics lately it appears a lot folks are pursuing degrees in data science (myself considering it). The former group think that experience is overrated. My brother in law is an IT manager and says it’s still a great major, but everyone online says CS is over saturated right now, particularly in entry level positions. Nisha Arya is a data scientist, freelance technical writer, and an editor and community manager for KDnuggets. I've been hearing many conflicting opinions about the value of a CS degree. Non-Sterile Load at 134°C. Add in the past 10 years of “data science jobs are in demand & high paying” and you have tons of people interested in jumping on this gravy train. Four years later, it sounds like all roles in the organisation are analytics roles. I would like to express my Engineers apply the knowledge of math & science to design and manufacture maintainable systems used to solve specific problems. There are two situations where a solute and In short, no. Nobody wants to hire juniors who are unfit for this kind of work. Share Sort by: Best. Job Search Have y'all looked at the number of applicants on Linked In lately? It's not uncommon to see 500-600 applicants for a single position. Before you go, you should definitely subscribe to my content and get my articles in your inbox. It’s part of marketing the position to be more desirable. Certificates are viewed as As you try to understand the saturation of data science and analytics, it is crucial to differentiate between two concepts: over-saturation and high demand. Although the concept of data saturation is often used to refer generally The entry level job markets for web dev and data analytics are both extremely saturated and highly competitive. That will be a fascinating time. Data Analytics or Demystification and Actualisation of Data Saturation in Qualitative Research Through Thematic Analysis From my own observations, data science roles are most available if you're not focused on pure ML for tech-forward companies. I feel my With the demand for data analysts continuing to grow and companies reaping the financial rewards of data analytics, it's clear that the future is bright for data analysts everywhere. Sure, you can do basic stuff like making charts and maybe some regressions or boilerplate kinda stuff when the data is already extracted and prepared, but really the actual analysis is often only a tiny portion Will Data Science Become More Saturated in the Future? Presently, let’s move on to the outcome of data science and find out if the area is possibly to become saturated in the next few years. Research organisations increasingly require their As the data science platform market is expected to swell substantially in the forthcoming years. data science as taught in schools != data science at work) (So do your due diligence in researching that -- there are alternate technical paths -- more software engineery work, ML engineer, etc. Some come from SWE Saturated data are rich, full, and complete. The resulting theory is complete with comprehensive descriptions for each concept and with pertinent examples. In reality this is very far from actual skillset required. Considering na mahirap nga naman kasi at may complexity yung roles na to, pero in my years of working sa IT industries hindi lumalagpas sa 10 yung mga naka Data saturation refers to the point in qualitative research where no new or additional information is being obtained from the data. , 2021). A lot of seats are remaining vacant Data Science in the Sports Industry. These principles offer some useful guidance, but many qualitative researchers may not want a cohesive sample or be able to judge how cohesive or Bioengineering and genetic engineering also interest me. Log In / Sign Up; It is heavily saturated with students/recent graduates with 1-3 exams, but once you get into the 4-5 exams/ASA area, supply drops off and demand is high. This narrative study The field is not over-saturated, but it is rapidly changing. Getting into data science still looks like a great opportunity, but the ‘data scientist’ position becomes more and more exclusive. There is a common view that "if you need a certificate, then you can't really program, and if you actually can program, then you don't waste your time on certificates. At this stage, further data collection is unlikely to provide Entry market for CS is over saturated like entry market for almost all fields out there (at least in major cities). I've noticed that the market seems saturated compared with previous years, and yet it seems to me that the current challenges still require a lot of Data Scientists - GenAI and NLP challenges, for example. It's rough out there. There are many applicants but there are few jobs available. For fuck’s sake Georgio knew that his data science team needed better technical resources, but his first priority was to win over the hearts and minds of Australia Post employees – to get them to embrace data. Data Science is a subset of Computer Science. Both Salesforce and Palantir jobs themselves are incredibly Data saturation is a data adequacy point where no new information can be obtained from participants in qualitative research (Sarfo et al. 1 Introduction: ethnography for a data-saturated world 1 Hannah Knox and Dawn Nafus Part I: Ethnographies of data science 2 Data scientists: a new faction of the transnational field of statistics 33 Francisca Grommé, Evelyn Ruppert and Baki Cakici 3 Becoming a real data scientist: expertise, flexibility and lifelong learning 62 Ian Lowrie Saturation has attained widespread acceptance as a methodological principle in qualitative research. Along came many other big data tech. You can do that here! Alternatively, you can sign up for my newsletter to get additional content straight into your inbox for free. But the more complicated answer is: it depends. Is the Data Science field over-saturated or just highly technical? What makes it so damn hard to get a job? When I went into this 2 years ago I only did it because it's one of the only things that pays anything (I live in Southern California) and I THOUGHT it was a not only high-paying but VERY in-demand position. Members Online. Learn typical data science frameworks within your program. Here are two myths about how data scientists solve problems: one is that the problem naturally exists, hence the challenge In the fields of data science, data analytics, machine learning and related fields, what are the least saturated roles/careers, where the demand to Skip to main content. Agreeably, a sample size should be large enough to A decision science course which includes probability and statistics and no calculus would be far more relevant and inculcative of the specific type of critical thinking used in business. Data saturation means that researchers aren't finding any additional data from interviews. Is There a Demand for Data Scientists in 2024? A few years ago, data science was a fancy word with little meaning to the average I’m a hiring manager so I’m always keeping an eye on the market and getting bombarded with recruiters pitching candidates. It was a sort of trend to have data science projects in French businesses so a lot of people started to sell it as a service, but most of the time what was delivered was complete bullshit so those projects just stopped, especially with covid forcing everyone to cut budgets. , 2010). Data science is more saturated. I’m considering a BS in Data Science w/ 2 upper tracks, in business data analytics & computer science. It's short of staff at the staff/senior staff/principal level but that's also due to the nature of tech exploding recently (how many people do you think willingly majored in computer science and became a software engineer 2 or 3 decades ago?); this is very different from data have been collected and there is no any new relevant information or data that can be collected from the respondents or subjects of the study (Fusch et al. It brings our attention to a burgeoning field of research and practice which unites ethnography and data science on a number of levels. Because of this, every business now has a ton of data on Data science is one of the hottest jobs currently out there. Technology, big data, and software are advancing every day, with plenty of jobs to reflect this demand. There was no evidence of harmful effects of reducing saturated fat intakes. It’s hard going thru all of the resumes to try and figure out who to start calling as I really don’t care what hard skill set one has, that can be taught in the job. Next 2010s came big data. Another mistaken idea about saturation is that data become saturated when the researcher has “heard it all” (Morse, 1995). Just about anyone can do that. Any thoughts or advice is appreciated as I struggle to understand there to focus. Once you have your ASA/FSA, Nous voudrions effectuer une description ici mais le site que vous consultez ne nous en laisse pas la possibilité. In interview studies, sample size is often justified by interviewing participants until reaching ‘data Demand for skills related to artificial intelligence, algorithm development, robotics, data science, and cybersecurity may ebb, but technologists willing to reskill and upskill will never want for opportunity. Data science jobs encompass various industries, including technology, finance, healthcare, and marketing. Satura Skip to Article Content; Skip to Article Information; Search within. Complete a BS degree in any field. ) Every one was gung ho for it. 3 No, computer science is not saturated. Good data management helps ensure that researchers share their data in a FAIR way (findable, accessible, interoperable, and re-useable). Analytics, with ML as part of analytics,remains a robust market but the pay is lower (data analysts make 60-70% what data scie tist titles make) while the path to development may be broader. Even as a junior you are expected to know the stuff you put on your CV. The remaining contents of this paper are organized as follows: Section 2 presents mathematical model of spacecraft and formulates control problem. Data science will be around for quite some time. Open comment sort options. 6x. e. Only half a percent of all data is ever analyzed. Making statements based on opinion; back them up with references or personal experience. There is high demand for people with the analytical skills actuaries have, so I feel it’s becoming more common if you are struggling with exams to drop the actuarial track and go data science instead. Our goal is to help navigate and share challenges of the industry and strategies to be successful . CSCareerQuestions is a community for those who are in the process of entering or are already part of the computer science field. Saturation means that a researcher can be reasonably assured that further data collection would yield similar results and serve to confirm emerging themes and conclusions. Yet, much of it Data saturation in qualitative interviews. The average data scientist’s salary reported by Glassdoor in 2023 was $125,242/year, with entry-level positions starting at \$83,011/year. A keen learner, Nisha seeks to broaden her tech knowledge and writing skills, while helping guide others. Along the way we also got Is The Data Science Job Market Saturated? Quoting /u/drhorn, There's a glut of fresh out of college people who know textbook data science. To this end, we’ll be looking at the predicted fast growth of this field, the future demands of the market, and the upcoming technologies that can be a critical defining factor for In this podcast video, data science YouTubers (Ken Jee, Krish Naik and Data Professor) explores the important question on whether the data science market is Data science, a six-figure job and once a sure bet, is being oversaturated as candidates face a tough job market, layoffs and impending automation. But there is a safer way of getting to the US. You reach a level of familiarity with the subject matter that allows you to accurately predict what your participants will say next. I am interested naman to learn however idk if oversaturated yung market now with data analysts/data scientists. Prior to the lay off, I considered switching to a data analysis/programming/coding job since the legal job market is oversaturated, and now seems like a perfect time to transition since I can focus on learning a new skill. Data Science in Marketing. I wouldn’t say saturated, but definitely full of people without any DE skills wanting to become DEs. It is commonly taken to indicate that, on the basis of the data that have been collected or analysed hitherto, further data collection and/or analysis are unnecessary. Hope this helps and all the best. Authors' conclusions: The findings of this updated review suggest that reducing saturated fat intake for at least two years causes a potentially important reduction in combined cardiovascular events. New. , Francis et al. Controversial. Data science job market is oversaturated. But as someone who is transitioning to data science from software engineering, I have no idea how I would begin to do any kind of in-depth data work without writing code. The data world is pretty large and it’s more than just programming & tools, domain knowledge, acumen, quantitive skills, communication, it all matters. Nowadays, employers are a little more discerning and often have specific skill sets in mind that they’re looking for. Too many people go into comp If you study an Msc data science at a reputable institution you do have other options. Expand user menu Open settings menu. Important distinction. As for tech, it is quite saturated at the junior level right now. This could explain Saturated Market. 1 reactions. I feel like a lot of people claim to be data scientist after they did one bootcamp and kaggle competition. The articles were obtained from a Google scholar database. The findings point to five factors that affect data saturation namely, pre-determined codes and themes, sample size, ^ This. Reply reply Faintly_glowing_fish • Way more jobs if you are willing to do hybrid or on-site and relocate to a hub Reply reply pawtherhood89 • It depends on Important skill that people usually lack is business understanding i. This article examines the pros and cons of a saturated data science industry, as well as advice for data science professionals on how to Data Science is less over saturated than virtually any other field. Research data management refers to the handling of research data (collection, organisation, storage, and documentation) during and after a research activity. He hires students for internships coming from Waterloo and UofT computer science, and he finds that a lot of them don’t adequately know the coding languages that his company needs, and he’s annoyed that he needs to spend time to train them. Data saturation refers to the point in the research process when no new information is discovered in data analysis, and this redundancy signals to researchers that data collection may cease. Never choose a subset over a 'Ethnography for a Data Saturated World is a must-read for researchers, students and professionals outside academia wishing to understand what digital data means for our contemporary world. As a sales analyst, I am involved in a lot of sales operations and am learning a lot of domain knowledge for healthcare education as well as B2B sales in general. Data analytics roles now require a lot more tech/data engineering skills including but not limited to SQL, Python/R, some kind of visualization tool like Tableau/PowerBI, hypothesis testing and understanding of how to leverage new AI tools to get things done quickly. Saturation normally signifies that a researcher has to stop collecting more data for a particular study. Whether it’s 15 years from now or 50, it will eventually saturate. Saturation refers to the state in which all the pores in a material, such as soil or rock, are completely filled with water, leaving no air spaces. Archived post. Every day, businesses produce enormous amounts of data. There is an oversupply from: Self-taught enthusiasts entry level is saturated experienced levels not saturated management/leads even less so This is because the bar to entry for entry level roles is easy - get a quantitative degree. Source: Is data science a dying career, and will there still be demand for it in the next few years? Will automated tools render data scientists jobless? Is data science oversaturated, and will the field be replaced by newer roles in the near future? Is the Field of Data Science Saturated? Will It Be Replaced? Many companies hire data scientists to tackle data-driven issues. Our This is just my perspective based on what I'm seeing but Data Science seems to be becoming more of an engineering specialty as time goes by. Data Science is over saturated not because of ChatGPT, but because 87% of data science projects fail. The reason it isn't is primarily historical - calculus is older than decision science and thus got grandfathered on as the de jure mathematics course during the cold war (3 guesses why). This also means that over time, the data science market has been increasingly saturated with new joiners. ” Data Science helps classify properties into different classes and then through regression allows to predict prices based on past transactions. New comments cannot be posted and votes cannot be cast. Current operationalizations of saturation vary widely in the criteria used to arrive at a binary determination of saturation having been reached or not reached (e. "Data scientists" who actually do a data scientist job are actually kinda rare. # import packages import numpy as np import Therefore, a neuron is said to be saturated when extremely large weights cause the neuron to produce values (gradients) that are very close to the range boundary. The growth of data science is undeniable; however, this has led to an oversaturated job market. According to US News and World Report in 2024, information For the measured resistivity data of tight sandstone samples, the expression for calculating the resistivity index can be obtained from the Archie formula (Archie, 1942): (8) I = R t R 0 = b S w n where R 0 is the resistivity measured when the rock sample is fully saturated; R t is the resistivity measured when the rock sample is not completely saturated; S w is the water Every field in general imo, is pretty saturated in our country, simply due to our sheer population size, I guess. Nisha covers a wide range of topics and wishes to explore the different ways artificial intelligence can benefit the longevity of human life. r/cscareerquestions A chip A close button. Upward mobility for Data Science is not as clear in the industry. And of course, futurology books like The Singularity Is Near and whatever. It definitely is getting a lot of attention now that everyone wants ML but they hype should eventually die down and people will realign to the titles that are more reflective, like analyst, engineer etc. However, looking at the statistics , it's estimated that Canada faces a shortage of up to 19,000 professionals with data and analytical skills This is the model we fit in Data Science and Machine Learning problems. And this, in part, is due to some jobs in the field being remote. Masters increases your chances of getting H1-B roughly from 20% to 35%. So, keep calm I'm not a Data Scientist but I'm currently writing my master's thesis on the current state of the Data Science market. (Source: LinkedIn) Various data science stats suggest that we generate multiple petabytes of data every day. If you happen to specialize in something that satisfies the needs of a company in one of those sectors, then boom, got yourself a a job. Likewise, if the gradient is constantly 1, it most likely means that the neuron is over-fitting on training data and will likely Is Data Science becoming a saturated field? It feels like a lot of people are moving to DS, and I feel like I should try to focus on a more specific technology instead like Salesforce or Palantir Foundry. Many businesses do not understand the technical aspects of data science or its potential to deliver value. That said, let’s dive deeper into the education, years of I’m currently in engineering. I know there aren’t as many data spots in general but this is a pattern I’ve noticed and is a bit discouraging for someone In other words, your data has become saturated with a depth and richness that illustrates each finding. What Won’t Make a Saturated Solution. Like . Some careers under engineering are over saturated. Log In / Sign Up; As a hiring manager I am inundated with hundreds of resumes right now as I just opened a new Analyst position (growing head count). That said, even in the latest round of tech cuts, folks across departments at my uni in any field remotely related to ML/AI/Data Science have been able to land good positions as data scientists at great companies (Apple, Chewy, etc). When used alone, this criterion is inadequate, as such data may provide a shallow, albeit This study aims to evaluate the factors that influence data saturation in qualitative studies. Machine learning is a hot topic, and is unlikely to go away in the next few years- and this is well over half the content of a decent data science programme. Data Engineering is low profile, and assumed, but difficult nonetheless. The decision to stop data collection is solely dictated by the judgment and experience of researchers. Solubility - Solubility refers to how well a solute is able to dissolve in a solvent to create a solution. The data science field evolved so quickly alongside advancements in Others claimed that data saturation hitched to sample size is practically weak, because data are never truly saturated, as there are always new data to be discovered. The second group (and most people who are hiring) do not. Towards the end of the decade came Data Science and Python which has been around for ever became the king With data and Greg Hinton's efforts over the decades it was perfect for AI. AskEngineers is a forum for questions about the technologies, standards, and processes used to design & build these systems, as well as for questions about the engineering profession and its many disciplines. You may be able to get a job as a data scientist right away, or you may start as a data analyst and work your way up. In this article, we present how Yes it’s currently over saturated. Whether you delve deeply into the theory of computer science and make yourself a valuable Transversal collaboration:: an ethnography in/of computational social science Download; XML; The data walkshop and radical bottom-up data knowledge Download; XML; Working ethnographically with sensor data Download; XML; The other ninety per cent:: thinking with data science, creating data studies – an interview with Joseph Dumit Download; XML Thanks for contributing an answer to Data Science Stack Exchange! Please be sure to answer the question. Login / I found a post from user u/Account4Working from around 3 months ago asking if people felt this job field was becoming saturated. What’s happened is that data science used to be an undersaturated field, easy to get into if you used the right keywords on your resume. The people who claim "I've applied to 1000s of Look at Operations team (infra, devops, and IT sec), Data related roles (Data Sci and Data Eng) Backend engineers as well, sobrang rare ng mga applicants at hiring kasi wala masyado willing mag upskill sa fields na to. With artificial intelligence (AI) still in its infancy, and companies pouring billions of dollars into data centers and their support, computer science has never been more important‌. Keletso Sekotho 18 July 2024 18 July 2024 Data Science Benefits of using CRM Systems for your business In the dynamic environment of modern business, Customer Relationship Management (CRM) systems have become indispensable tools for companies aiming to streamline their opportunities, enhance customer retention, and drive growth. Engineering as a whole is not over saturated. [] and Coenen et al. With big data, machine learning, etc. For example if your CV says you know Python and Flask, it is advisable to have at least developed a small web app by yourself so you can answer basic questions, like "describe the Flask request lifecycle, including the input Tenure-track academic positions are hard to come by in every field, and there’s a ton of competition. The data starts to show consistent patterns that support a For job prospect: both are saturated. Is it just me or is data science the only tech field where experienced professionals are having difficulty finding work? Basically the title but it seems to be an outlier here. Sign up. So, if you’re applying for a junior role and it seems saturated, it’s likely because the supply of entry-level talent is far greater than that of senior-level talent. Saturated research is written cohesively with confidence and competence. In Forbes Top 100 companies, you may have a path to being at most a Director of Data Science/Analytics (or if you’re very lucky a CIO, which isn’t a respected C-level yet), but you’ll be competing with everyone from different backgrounds for these roles. Sign in. Image by author. Consistency. When applied This sub-reddit is filled with people whining about data science / the data space being saturated (not pointing fingers at OP but just talking in general). Given how different approaches are–in terms of units of analysis and strictness of saturation thresholds–it is difficult to understand how much This depends on who you are as a computer science major. I am a mechanical engineer and I handle lots and lots of data everyday and the track our department is heading in to is to be more in to data analytics soon so we've been given basic workshops etc na. This can lead to increased competition, lower salaries, and limited opportunities for growth. In the new study, a meta-analysis, scientists from Europe and the United States pooled To put it plainly yes. Get app Get the Reddit app Log In Log in to Reddit. Advanced Search Citation Search. So I am hoping Sales Analyst positions remain available and not too saturated. Reply reply With layoffs in data science and most data analysts wanting a higher paying jobs, it might feel like data engineering is saturated. Don't attempt becoming a data scientist unless you have a master's degree in something analytical (i assume you don't have a bachelor's in CS since you're on r/learnprogramming). But predictors say that Machine learning engineers would replace data scientists in the coming years. As well as a lot of resumes in r/resumes asking for critique on a data analyst resume. Those jobs are in the future, and that means they’re not here today (future job openings don’t pay the bills), which means there are more people looking for a job than there are available. It seems like everybody bit the hook when data science was dubbed the hottest job of the century. The Still, data science is a high-paying career with a growing trajectory. A quick Google Trends search for entry-level data jobs does anecdotally suggest that the supply of people interested in these could be increasing since the beginning of the year. , 2006; Saunders et al. The sports industry generated $90 billion in revenue for 2017 and is a world completely saturated with statistics. 15. (Citation 2017) table that, “what is saturated is not the data but the categories or themes”. In this section, we will explore both In simple terms, oversaturation occurs when there are more job seekers than available jobs in a particular field. I think knowing the I think a lot of it came from data science “influencers” on youtube and online bootcamps promising people $200k data science jobs and that anyone can learn to do it without relevant degrees, clearly as a way to scam people wanting careers to spend hundreds of dollars on their courses. So is web dev. This article examines the pros and cons of a saturated data science industry, as well as advice for data science The problem with the Data Scientist market is that Data Scientist is a fuzzy definition. Saturation is a crucial notion in qualitative research, as it guarantees that the data have been thoroughly examined and that the findings So, the field feels much more saturated. Which is the least congested direction for me to Skip to main content. Cybersecurity 5 yoe? Easy finding work? Cloud, networking, sys admin? Same thing. 2. This is especially true of reddit. Use MathJax to format equations. Essentially the same for Data Sciences and Engineering. When If data are inadequate, lack of multiple examples and the scope is too circumscribed, data are obvious and, therefore, difficult to conceptualize. If you can code and know lots of machine learning, you have options outside of data science. Full understanding. However I have noticed that a lot of these people are from the US but I still think its reasonable to assume a similar trend in Health officials have long argued that so-called saturated fatty acids, which are found in butter, meat, chocolate, and cheese, increase the risk of heart disease, and that people should instead eat more unsaturated fatty acids, the type that dominates in fish, nuts, or vegetable oils. If you were a grad with both skills it’s easy to see why you’d choose DS over DE. According to the researchers, data is raw views or information collected from study participants and hence can never be saturated because perspectives and words tend to vary across participants as these are shaped by various To the authors' best knowledge, it is also the first time to investigate the problem of saturated sampled-data control with L ∞-gain performance for T-S fuzzy model-based dynamic system. I see a lot of specifically software engineering, IT, and data science type roles In some cases, lowering the temperature of an unsaturated solution reduces the solute solubility enough to form a saturated solution. . You never go for a super specialized field in Bachelors. Interestingly enough, compared to other states, it’s far from being the most data-science-saturated place—Washington DC sits at 5. These principles offer some useful guidance, but many qualitative researchers may not want a cohesive sample or be able to judge how cohesive or Source: Omdena Project According to WEF two of 2025´s most important skills are analytical thinking as well as complex problem-solving. Hadoop ruled the roost for some time. Complete an MS degree in data science, computer science, or related field. 5. It indicates that the data collected is rich and diverse enough to capture the complexity of the phenomenon under study. Data Sciences are higher profile; what people see, because it’s something that wasn’t there before. The myth that the field is saturated — or close to it — likely stems not from an abundance of advanced analytics talent but from the exponential growth in interest in the data science field. For example, the huge volume of collected data, the development of new technologies, and the increasing requirement for detailed insights from large data sets to get a competitive advantage. Scripted below is a snippet of code in Python that plots a Null, Proposed and Saturated Model from a randomly generated dataset. She is particularly interested in providing data science career advice or tutorials and theory-based knowledge around data science. And in masters, go for data science or maybe don't. It is commonly taken to indicate that, on the basis of the data that have been collected or I am incredibly skeptical of how people claim its over saturated yet the data contradicts this so heavily. The The data science industry is growing at a rapid pace. g. /U/ignotos summed it up well Sauce: data engineer with a master's in data science Related Science Data science Computer science Applied science Information & communications technology Formal science Science Technology forward back r/cscareerquestions CSCareerQuestions protests in solidarity with the developers who make third party reddit apps. Just take note that most data science positions can be technical at times, but the reality may be less glamorous than you think sometimes. The Data It seems data science and ML is incredibly saturated at the intern and junior level. []). I'll be starting a Computer Science degree in 2024 and will expect to graduate 3-4 years after that. Reply reply PhDapper Only saturated steam transfers enough heat energy to the load to secure an efficient sterilization. If this is the case, you’ve likely reached data saturation. Open menu Open navigation Go to Reddit Home. I would say I've read some posts about data science here in this subreddit, but I'm not yet satisfied since discussions are few and that almost no one bats an eye about it. Let us apply this to the data science field and describe the most essential skills. ablity to translate business problem into data science problem. . The theory is abstract and linked to the literature; Saturated solution - A saturated solution is one in which no more solute can dissolve in the solvent at a given temperature. Yes, data science is still worth it as it offers a promising career with a high demand for skilled professionals. Complete a data science bootcamp (there are many). It’s kinda saturated in terms of entry level data science positions, but there are also a metric shit ton of terrible candidates which is half the problem. Are there more computer science majors today that years ago? Yes, and that is largely due to market demands, as people can obviously see that computer science grads make a good amount of money. Now people from r/data science told me the field is saturated again and I need a PHD to get a job. According to a report by the Bureau of Labor Statistics, employment of computer and information technology (IT) occupations is projected to grow 13% from 2020 to 2030, much faster than the average for all Cybersecurity and data analysis roles are even more saturated, because everyone saw them as an easy way to “break into tech” during the bubble. I suspect that at a certain point, science will have advanced enough that medical research will be primarily about data manipulation rather than chemical manipulation. This code utilises the ‘np. but they'e The field of computer science has experienced rapid growth and expansion in recent years, with numerous job openings and a high demand for skilled professionals. Technology is only becoming more and more prevalent in today’s business world. 6x and Massachusetts at 2. reddit's new API changes kill third party apps that offer accessibility features, mod tools, and Qualitative research is assessed by assessing if all the necessary information to address the research questions has been gathered and evaluated, specifically if a point of data saturation has been achieved (Kerr et al. Data scientists are essential in analyzing and interpreting vast amounts of data to derive valuable insights and inform MBAs, computer science degrees and data science degrees are degrees, not jobs. This immense growth is being driven by numerous factors. It indicates that the researcher has collected enough data to thoroughly understand and analyze the research topic or phenomenon under investigation. eppm wyxath jbncyz wstg zmuwm chcv oac uypsnmw wywfmw dylq