| I’ve posted nearly 600 data & research jobs since early 2024, but I’ve been posting more of these roles in 2025. In 2024, I posted roughly 90 jobs each quarter. In 2025 – I posted more than 150 in the first three months of the year. While the number of jobs has slowed a little from that peak, I am still posting over 40-45 jobs a month in this field — and most of these roles are looking for 2-5 or 5-8 years of (relevant) experience. When I last wrote about data and research jobs just about a year ago, I focused primarily on upskilling for these roles because many of you have experience doing social science research as part of an advanced degree and/or have used Excel extensively to analyze educational data. In this newsletter, I’m going to focus more specifically on the types of data roles I routinely see and dive into the larger career trajectory, from early career to director level roles, considering what skills and tools you need to know as well as what types of tasks you’ll do in these roles. My goal is to help you prepare for the next level of your career regardless of your current role. I’ll focus on two of the three largest categories of data and research roles I post: research positions and director and VP-level roles (the latter represent nearly 20% of the data/research roles I post overall!). I’ll also spend some time on roles that I post less frequently but do still post regularly. Here, I’ll be focusing on the categories that each represent more than 5% of the total number of data/research roles: policy roles, data engineer roles, data scientists, and business analysts. I’m not going to talk about Data Analytics roles in this newsletter mostly because this newsletter is already over 3,000 words! But it’s also a category where I feel like there’s more information about how to transition into the field — including specifically from teaching roles — so I want to share more on the subcategories we’re hearing less about. That said, a quarter of the data and research roles I post are data analytics roles so it’s a good field to consider if these roles pique your interest. I know at least one math teacher has recently moved into a data analysis role, for example! TABLE OF CONTENTS Research Jobs: Career Pivoter & Early Career Roles Research Jobs: Mid-level Roles Policy Roles Business Analyst / Business Intelligence (BI) Data Engineer Data Scientist Senior Management Roles — Director and VP in Data and/or Research Do You Need a Portfolio When Applying to Data or Research Jobs? SKIPGATE The Remainder of this article is for Paid Subscribers. You can subscribe here and access the newsletter archive as well as find jobs at 500+ remote edtech/ed adjacent companies. SKIPGATE Research Roles About 25% of the roles I’ve posted in the larger data and research category fall under the “research” umbrella, and hiring for these roles is fairly steady — I post about 25-30 a quarter. These roles conduct educational research with k12 or higher ed students, manage research projects, and use data to evaluate the effectiveness of programming. Research topics include evaluating the effectiveness of an edtech product, assessment or intervention or evaluating significant research questions related to education (school financing, educational laws, equity, student performance in specific subject areas, mental health, etc). Some roles involve more research and report writing while others involve providing technical consulting/training to an organization’s partners. All will involve project management responsibilities but some roles also do this part of the role almost exclusively. These are great roles for anyone who wants to be part of evaluating and finding solutions to our biggest educational challenges! Career Pivoter & Early Career A third of the research jobs I post are open to Career Pivoters or Early Career employees who have experience in educational research, either in academia (so those of you with PhDs or master’s degrees in a education or a related social science field) or at an edtech/edjacent organization. If you’re pivoting into this category, don’t let job titles trigger imposter syndrome. I posted a Senior Research Scientist role last year that was looking for elementary/middle school teaching experience and an education-related doctorate. (And it paid six figures!) Many of these research jobs are looking for similar experience — having a combination of practical on-the-ground experience (in k12 or higher ed) and research training (which doesn’t have to be a terminal degree — a master’s degree is often looked for too) is a powerful combination. Edskippers with an EdD or a Phd should definitely consider research roles, however. You want to target these early career/career pivoter roles unless you have additional research experience outside of academia. At this level, I see multiple research roles that are looking for either 2+ years of experience or a social science master’s or doctorate degree. Why? Because you have training and experience collecting, managing, and analyzing qualitative and quantitative data. If you’re looking for roles that leverage your master’s degree and still pay well, search for “research associate” — these regularly pay $60-75k a year (and I saw internships in this range that started in the $50-60k range). With a doctorate, the median salary was between $80-90k. These are all starting ranges, and, as you can see in the next section, salaries continue to grow as you gain experience. Most of these roles require tools and techniques that are probably already familiar to you — conducting literature reviews and writing research reports, designing surveys and analyzing survey data, and managing research projects. Some roles additionally require more quantitative skills — the ability to collect, analyze, and interpret educational data. About 20% of the roles that I had full job descriptions for required knowing programming languages or statistical software (Python or R) or using SQL. The remainder were looking for general research skills, knowledge of statistics, and experience managing data in Excel. Research roles vary widely in the types of tools and experience you need. What is more important in these roles than the specific tech stack you use is your ability to identify and share compelling data stories. Your experience in education helps you understand why a specific data point is the most important to pull out and why others may feel right but don’t actually explain how students learn. Your experience also helps you more effectively validate the data you’re analyzing. You’ll be able to identify when a statistic sounds impressive but is really just … bluster. As you’re preparing application materials, especially for your portfolio and for interviews, think carefully about what kinds of questions you ask before you start to look at a data set and then how you select the most relevant data. Be prepared with specific examples where you’ve had to select the best data and present it to others to make better decisions with or even make recommendations based on the data you collected. Mid-Career Roles Mid-career roles in research typically pay between $70-100k for up to 5 years of experience or $100-120k for 5-8 years. These roles make up just about 2/3rds of the roles in the research category. (This does not include Director/VP level researchers because I separated them into a different category!) Candidates at this stage of their career are doing very similar tasks as the career pivoters, with more of an emphasis on conducting new research rather than summarizing existing research. Projects become more complex and data sets become larger — or are collected from multiple different sites. There’s also an increased emphasis on using data visualization tools to report on the data, which makes sense because these data sets are larger so finding ways to clearly show trends requires more complex skills and tools. As with the previous category, experience working with educational data is important but I see fewer references to needing on-the-ground teaching experience in this category. Edtech/edjacent organizations do assume you have worked with educational data, however. Because the data sets grow larger, there’s more emphasis on statistical software skills in this group of listings. Even so, Excel dominates the tools list that a researcher needs — about 40% of listings (with job descriptions) asked for this experience. (This is true for data roles more generally — in edtech and outside of the industry, Excel is still the primary tool used for a quarter of the jobs) As I mentioned last year when I wrote on this topic, if you’re interested in this field, leveraging your current Excel skills and learning how to write more complex formulas is a crucial first step to transitioning or advancing in this field. That said, 10-20% of the roles also were looking for more advanced tools so you’ll need to upskill for some roles. Again, if you’re looking to advance in this field, focus on mastering Excel and then begin building out your tech stack. Instead of learning tools for the sake of learning tools, learn the tools you need to answer more complex questions. This helps you strategically respond to research needs and prioritize solving problems, both of which reflect a strong ability to think like a data analyst in a business setting One question I often hear is whether a PhD is required for these roles — the answer is that it depends! For the jobs where I had summaries or job descriptions, about a third of the jobs looking for 2-5 years of experience required (or preferred) a doctorate while about half of the roles looking for 5-8 years of experience did. When these roles require an advanced degree, they are also usually looking for experience in the field so these roles, unless they’re on the 2-3 years of experience side, are not a direct-from-a-doctoral-program moves. Other Data or Research Roles I Post Regularly For these roles, I’ll be focusing on the categories that each make up at least 5% of the jobs I post in the overall category. Data Science and Engineering roles require more technical skills while BI roles require often require business operational expertise in addition to analytical experience; policy roles, while not a direct-from-teaching role, are very similar to research roles in terms of responsibilities and skills needed; the major difference is they typicallydo not require a terminal degree. In total, the next four roles I’ll talk about make up about 20% of the jobs I post overall. Policy Roles Most of the policy roles I post are looking for at least 2 years of experience in the field. The exceptions are internships/fellowships which I do post a few times a year. These are paid — the fellowships ranged from $50-80k (with the caveat that most of them were at a single organization, The College Board, so the rate was the same). Policy roles are essentially research jobs that focus on governmental policies — in fact, most of the roles I posted in the 2-5 year category involved research. The reason I separated these jobs from research jobs more generally is these roles are more often looking for policy research experience not just general research skills. That’s because educational policy is governmental policy so it’s important to be able to find governmental documents and be able to interpret the specific policy nuances and exceptions and explain them clearly. And then, when those policies change in the next legislative cycle, you have to track changes and update all your documents! These roles typically paid between $69-82k (the exception were Senior Policy Researchers/Analysts who were closer to or above six figures). As I mentioned above, most of these roles do not require a PhD so if you have a graduate degree where you did a lot of educational policy research, you should be looking at the 2-5 year jobs! Senior Policy Analysts and Principal Researchers typically have 5+ years of experience in the field. The median salary for Senior Policy Analysts was only modestly higher than more junior staff — $76-93k. But senior level staff here were earning in the mid-six figures. As you move into this level of experience, the job often includes research still but the role also is responsible for developing and implementing a larger policy agenda for the organization (or making recommendations for that agenda in a larger organization). Business Analyst / Business Intelligence (BI) Business analytics is a subset of data analytics but it’s focused on using internal data to improve operations and procedures. For example, many of the jobs I post are looking for candidates who will use data to: “improve sales efficiency and productivity,” “improve school district invoicing and schedule efficiency,” “conduct market research,” “analyze user stories” (to advise on implementation processes and solutions), or simply maintain all business data so you can answer questions specific departments might have (“why is our churn higher in medium-sized districts compared to smaller and larger ones?,” “how can we reduce onboarding time for new clients by two days?,” “do we need all these different subscriptions our employees are paying for?,” etc). These roles typically require analytical and statistical analysis experience — sometimes that’s more specifically business analytics rather than analytics in general. If you’re coming from a graduate program rather than industry, look for job descriptions that focus more on tools and skills than that business operational knowledge and insight. Python and/or SQL as well as visualization tools were required for almost every job (as always, for the jobs where I had job summaries/descriptions)! The major difference between roles looking for 2-5 years of experience and those looking for more than 5 was that the more senior level roles started to expect more niche experience — so specific technical platforms (like SIS or LMS) or financial analytics in addition to business. Most of these roles were still looking for edtech/education SME as well but they needed people who could offer immediate insights into their existing workflows and systems. Median salaries for 2-5 years of experience ranged from $78-120k while 5-8 years of experience was only $90-121k! Candidates with at least 8 years of experience were making $120-150k but I only had a few data points there. Data Engineer One of the questions that I hear most often is: what is the difference between a Data Engineer, a Data Scientist, and a Data Analyst? Data Engineers focus on creating the data architecture that Data Scientist and Analysts use to build insights. This means connecting to APIs to gather all the data the company uses, managing all that data in data warehouses, and making sure the data is clean and usable. But there is sometimes an overlap between analysts and engineers — some companies even combine the role or assign SQL querying/reporting duties to an engineer. This is a role that pays quite well — though I didn’t post many early career roles, the ones I did post started at six figures. More typically, this role paid between $120-150k for up to 8 years of experience and $150-175k for more. If you’re interested in data engineering roles that are looking for 2-5 years of experience, you’ll often find that analytics experience — or software development experience — is an aligned field. Understanding data pipelines and data warehouse models is essential for all of these roles in addition to being able to query SQL databases. The major differences that I saw between the early-mid career roles and roles looking for at least 5+ years of experience is that the latter were more frequently managing teams or coordinating with external partners to manage their data. Data Scientists In contrast to data engineering, Data Science roles are rarely combined with analytics even though they are both analyzing data. (The one exception is mid-level manager roles, which often supervise a analytics and data science team.) So that brings up the question, if they both analyze data, what exactly makes them different types of roles? The key difference is that analysts typically focus on using past data to make sense of trends or situations while data scientists typically focus on using that data to predict future trends; so data scientists focus more on creating statistical models and algorithms that help process and analyze data. This explains one reason why data science is one of the few data and research categories that often requires experience with machine learning and, for Data Scientist jobs that sound very similar to Data Analyst jobs, this can be a great clue for whether it’s going to require more sophisticated statistical analysis or not! How do you break into Data Science roles? The 2-5 year roles are definitely a good fit for folks who are coming directly from a phd program — while a handful of data scientist roles in general required a terminal degree, many were looking for either experience or a “relevant graduate degree.” Because the job requires more advanced statistical methodologies, this is definitely a role where you need to be experienced in Python, R, SQL, statistical models, and data visualizations as well as (often) machine learning and data infrastructure systems. These roles pay for the experience they’re looking for — 2-5 years experience has a median salary range of $108-142k and more than five years ranges from $115-167k (but up to $180 for more than 8 years of experience). Though more experience definitely nets more money, most of the roles in this job category (57% of them in fact!) were looking for candidates with 2-5 years experience or that relevant graduate degree. Senior Management (Director and VP-level Roles) While I’ve separated data and research roles in the above analysis, I’m defining senior management roles as any director or VP-level role whether it’s overseeing data folks or research folks or even policy! Many of these roles are overseeing all of these discrete functions. One example would be a “Director of Impact” whose overseeing research and data analytics into the effectiveness of their programming. You’ll also see titles like “Director, Research, Evaluation & Analytics.” At this level, you’ll also find Partners or Strategic Advisors who consult with a variety of partner organizations. As I mentioned above, these roles represent about 20% of the total roles on the job board. When we’re talking about these roles, we’re typically talking about roles that are looking for at least 8+ years of experience. A bulk of the career pivoter roles were also looking for 10-12+ years of experience, just explicitly in a school or university setting rather than industry. (Usually these were looking for k12 district-level experience or higher ed experience.) Surprisingly, about 20% of the Director level roles were only looking for 5-8 years of experience and another ~10% were looking for folks with only 3-5 years of experience. That’s a weird data point so I’m going to start by explaining what I’m seeing in those roles that are looking for much less experience! This was not a large sample size — there were only 7 roles total but they were explicitly Director or Assistant Director-level roles: “Director of Evaluations,” “Director of Impact,” “Assistant Director of Research & Writing,” and so forth. Half of them paid six figures while the other half started lower. What did they all have in common? They were looking for candidates who had experience working with large-scale data — district-wide, and typically from multiple districts. So here the company cared less about how many years of experience candidates had so long as they were accustomed to working with a lot of data. Another thing that stood out to me is that none of these roles asked for a doctorate degree. That’s a trend that stood out in this category more generally — despite these being senior level roles, only 15% of them required a terminal degree. That’s in sharp contrast to the roles that required less experience. Why? My guess is that we’re seeing the impact of more highly qualified candidates entering the market. Whenever that happens, companies can lower salaries or raise required experience (and sometimes they do both…). But the bank of senior-level candidates who entered in a different hiring environment would not necessarily have those same degrees so it’s not a criteria they can expect reliably at that level. Over time, I suspect we’ll see more Senior Management roles looking for advanced degrees in addition to direct experience in the field. In general, these roles paid a median salary between $120-144k. I didn’t see significant differences between directors who were supervising data teams versus research teams and, as I mentioned earlier, many of these roles are doing both. Do You Need a Portfolio When Applying to Data or Research Jobs? If you’re interested in moving into data and research jobs, most of the folks in my audience have an edge because of your master’s degree in education. That means you probably have writing samples of literature reviews or policy recommendations and examples of real world data questions you’ve answered in order to understand (and solve!) specific educational problems. Not every job is going to ask for a portfolio explicitly (I can tell you they certainly don’t mention it in the job description!) but you will be asked to talk about (and maybe even share) specific examples during an interview. And many jobs will ask for a writing sample in the application. So it’s worth pulling these examples together so you can talk about them easily. Once you’ve done that, also add them to your LinkedIn profile — then talk about them in a LinkedIn post (or series of posts). This can connect you with people who are passionate about solving the same types of educational problems that you’re interested in solving. Just the other day, I posted on LinkedIn about how recruiters were using AI in hiring and someone posted a link to a paper she’d written on that subject. I loved seeing this because it brought additional authority and examples to the conversation. Look for places to participate in these types of conversations, showing off your knowledge but also inviting others to learn more about something they’re curious about. |
Data and Research Jobs in Edtech/Edjacent Organizations
I post over 40-45 jobs a month in the data and research category — and most of these roles are looking for 2-5 or 5-8 years of (relevant) experience.
