So you want to break into data science. But here¡¯s the catch: most job descriptions scream ¡°5+ years of experience¡± even for junior titles. Not exactly beginner-friendly. The good news? There are real entry-level data science roles out there that don¡¯t require you to be a math prodigy or have already built a machine learning empire.
With the right skills (and some strategy), you can land a first role that puts you on the data science career path. Let¡¯s look at what those roles are¡ªand how you can get from zero to hired (while maintaining your sanity in the process).
Why entry-level data science roles aren¡¯t as mysterious as they look
Every company has data. What they often don¡¯t have are people who can make sense of it. That¡¯s where entry-level roles come in. These positions focus on cleaning, organizing, and analyzing data to support more senior data scientists and business teams.
Translation: you won¡¯t be building the next ChatGPT from day one, but you will be solving problems that actually matter¡ªlike helping a marketing team understand which campaigns are working or making sense of customer trends.
And the best part? These roles give you hands-on experience while building the foundation for bigger titles down the road.
Before we dive into a list of entry-level data science roles¡
Let¡¯s talk about the skills that actually get you hired. If you¡¯re brand new to the field, one word you¡¯ll hear a lot is Python. No, not the snake¡ªthe coding language that powers almost everything in data science. Python is how you wrangle messy spreadsheets, run analysis, and even start building machine learning models.
Once you¡¯ve got a foundation of Python skills, you can add tools to level up: learning analytics to interpret business data, practicing visualization to tell clear stories with numbers, and¡ªwhen you¡¯re ready¡ªtackling advanced concepts like predictive modeling. That¡¯s why we offer multiple learning paths.
A short course in Python helps you get comfortable with coding basics. A data analytics short course introduces the business side of data. A data science short course lets you build more complex projects. And if you¡¯re serious about making data your career, our immersive data science bootcamp is where you go all-in.
Now, what you¡¯re really here for. Let¡¯s break down the five entry-level data science roles that can help you put those skills to work.
The top 5 entry-level data science roles
1. Data analyst
Probably the most common entry point. You¡¯ll collect, clean, and analyze data to help teams make better decisions. Expect dashboards, SQL queries, and translating numbers into insights that actually make sense.
2. Business intelligence (BI) analyst
BI analysts design reports and dashboards to track KPIs, performance, and trends. You¡¯ll make sure execs aren¡¯t just trusting their ¡°gut¡± when setting strategy. Tools like Tableau or Power BI are big here.
3. Junior data engineer
These roles are about infrastructure. You¡¯ll help build and maintain the systems that move data from point A to point B. Less analysis, more making sure pipelines don¡¯t break.
4. Research assistant (data-focused)
Hospitals, universities, and labs often hire research assistants to wrangle datasets, run experiments, and present findings. It¡¯s not always glamorous, but it gives you hands-on practice in real-world data environments.
5. Junior data scientist
Sometimes companies do open up ¡°junior¡± scientist roles. They¡¯re often analyst-adjacent, but with light exposure to modeling or machine learning. Usually you¡¯ll be working under the wing of senior data scientists.
How to build your data skills (without wasting time)
There¡¯s a lot of noise out there: free YouTube tutorials, coding challenges, bootcamps, ¡°data science in 30 days¡± promises. Here¡¯s the real talk:
- Data workshops = get your foot in the door with the fundamentals. From basic Python skills to data analytics and visualizations, this is your starting point.
- Data short courses = great for resume boosts, skill gaps, or dipping a toe into data. They¡¯re ideal if you want the skills, but aren¡¯t ready to commit to a full career change.
- Data bootcamps = your best bet for transitioning careers. They give you structure, depth, and career services you can¡¯t get from DIY learning. And with us, you get full-time and part-time options.
We¡¯ve seen it firsthand. Take Jordan’s success story, for example¡ªa GA grad who used our bootcamp to pivot into data science while juggling real life. Proof that it¡¯s possible.
What to expect once you¡¯re in the door
Entry-level data science roles aren¡¯t necessarily glamorous, but they¡¯re absolutely essential¡ªand they¡¯re the launchpad you need. You¡¯ll spend time cleaning messy data, wrangling spreadsheets, and building reports that drive decisions. That grunt work? It¡¯s how you build the foundation for machine learning, AI, and senior-level titles later.
Stick with it, keep learning, and soon you¡¯ll be leading projects instead of just cleaning datasets. And along the way, you¡¯ll discover whether your path leans toward analysis, engineering, or advanced modeling.
Where GA fits into your data career journey
- Start small: Test the waters with a beginner Python workshop or data workshop to get a feel for the skills you need to succeed in a data science career
- Go deeper: Build analysis and visualization skills in our data science short course, or strengthen your coding skills in our Python programming short course
- Go all-in: Transition your career with our immersive data science bootcamp
Still deciding if data is your lane? Check out our blog on data science vs. cybersecurity to weigh your options.
The bottom line on breaking into an entry-level data science role
Breaking into data science isn¡¯t about skipping straight to ¡°data scientist¡± on LinkedIn. It¡¯s about starting small where you¡¯re at, learning the fundamentals, and building from there.
Entry-level data science roles like analyst, BI analyst, research assistant, and even junior scientist can give you that first break. The right training¡ªwhether it¡¯s a short course to boost your skills or a bootcamp to transform your career¡ªcan make the leap possible.
Not sure where to start? Browse our data courses and choose the path that fits your goals¡ªor reach out if you need someone to talk it over with.
Your first step into data science doesn¡¯t have to be perfect. It just has to be a step.