18 Data Science Jobs You'll Land After Bootcamp

Table of Contents

• 18 Data Science Jobs You Can Land After Bootcamp
• What Do Data Scientists Actually Do?

The spectrum of data science jobs is broad – everyone from governments to businesses to non-profit organizations are collecting data. But it takes Data Scientists, Data Analysts, and Data Engineers to turn that data into smart business decisions. If there’s one thing we’ve learned from interviewing so many data science bootcamp graduates, it’s that no two companies use the exact same job titles.

A data scientist at a startup may be doing data engineering, data cleaning, and data analysis. Someone with the same job title at a large consulting firm may be working with clients to build dashboards for their teams. Regardless, the data job market is growing and maturing, so the hard work of a data science bootcamp pays off: the average salary for Data Science Analysts is $80,265, while the average salary for Senior Data Scientists and Data Engineers is $105,909. Here are the data science jobs that bootcamp grads are landing every day.

18 Data Science Jobs You Can Land After Bootcamp

Below are some common job titles you’ll come across in your job search:

Senior Data Analyst and NYC Data Science Academy bootcamp graduate Jonah shares his advice to anyone on the data science job hunt now: 

• "Almost every company has openings for data scientists or data analysts. I would advise folks to reach out to people in their existing network working at companies of  interest with these openings and ask if they'll refer you to open positions. Networking in that way is what helped me land my job." - Jonah

What Do Data Scientists Actually Do?

All kinds of things! Let’s check in with 12 data science bootcamp grads (and a data science recruiter!) to hear what they’re working on:

Former lawyer Indre is now a Decision Scientist at Vinted, thanks to Turing College's Data Science Bootcamp.

• "Decision scientists are similar to data analysts. We work in cross functional teams with engineers and product managers and help make decisions based on data. We’re 'decision scientists' because we search for all the answers through data, propose them to the whole team, then make a decision based on insights from data. We're related to data science but we mostly work on analyzing, AB testing, and machine learning." Read more.

Lighthouse Labs graduate Mauro is now a Data Analyst at Rogers Communications, but has also been a Data Scientist at other companies. Here's how he breaks down the differences between these roles:

• "As a data analyst, you don't need to do prediction or work much on the data because there’s a data science team to work on and prepare the data. I just report my findings. A data scientist needs to understand how to work the data, like find more fields, and information to add into the machine learning so they can help make predictions." Read more.  

Zack switched into fintech and blockchain through Jigsaw Labs' Data Engineering Bootcamp. 

• "I aggregate transaction data from multiple blockchains, unify them, and deliver them to the Finance team for review and analysis... I typically use Python, Pandas, and SQL/Postgres every day." Read more.

After an internship through Jigsaw Labs, Aaron landed a Data Engineer role at cryptocurrency company, Cred Protocol. He explained to us what a typical day looks like for him as a Data Engineer:

• We start every day with a quick standup. Some days we'll take a longer standup to go more in-depth on issues people are having.
• We're on Slack all day doing huddles (voice calls), handing off CSV files to each other, and pointing out problems in the code. It's a huge collaborative effort!
• The hours fluctuate based on the progress of the assignment. Sometimes a task takes 2 or 12 hours and you just have to stick with it until it’s done. 

Read more.

Former marine biologist Mike enrolled in the UT Austin Boot Camps to make a career change into data analytics. He's now a Data Analyst at Booz Allen Hamilton.

• "For our clients, we’re working on cloud migration, data engineering, and building ETL pipelines. We also focus on creating data visualization components using Tableau dashboards. I have a fun job where I get to do every aspect of a whole data pipeline, which not everyone gets to do as a data scientist." Read more.

JK Kang became a Data Engineer at KPMG after graduating from Springboard’s Machine Learning Career Track. 

• “I’m working on a team that provides IT consulting to firms who may not have the resources to be able to architect or deploy certain solutions in-house. We visit companies who might not have a dedicated tech team (perhaps in the finance, insurance or medical fields), evaluate their way of doing things, and work towards architecting a big data solution for them, according to their business needs. This might mean going to a regional supermarket chain that is using a very siloed data solution and wants to change this. We leverage our knowledge and subject matter expertise to improve their solution.” Read more.

Inna is a Data Scientist at Nextail Labs in a consumer-facing role after graduating from IE Data Science. 

• “Going into the bootcamp, I knew I wanted to be a Data Scientist but I also knew that I wanted a client-facing job. I’ve been a Data Scientist at Nextail Labs for about eight months. At the moment, my role is to make sure that we can show our customers how we add value to their companies. I extract the data from our databases, analyze it in Jupyter Lab (using Python) and prepare datasets and dashboards so that the data can be accessible without any coding knowledge. Then, I get to present the results to the customer and work closely with the customer to make sure we are considering all the factors that are important to their business.” Read More.

Lynn Hodak, Corporate Recruiter at Capgemini, has hired more than 10 Metis data science bootcamp graduates “for Data Science, artificial intelligence, and analytics in Chicago, New York, and California.” One example is Sukeerthi Varadarajan, who is a Senior Consultant – Data Scientist. Read more. 

Logan is a Machine Learning Engineer at Hustle after graduating from Galvanize. 

• “It’s only been a few months, but a lot of what I learned at Galvanize I’ve been able to translate to my job, like knowing different model trade-offs and methods. I work a lot with Natural Language Processing (NLP) since we work with text messages. People call data “the oil of the information age” and while it can be used in terrible, terrible ways, it can also be used in some pretty amazing ways to benefit people. I’ve had the ability to follow a moral compass in my career. It’s not easy, and not everyone gets the opportunity to do it, so I feel very lucky to be able to include that in my decision making process.” Read more.

Nathan is a Data Scientist/Software Engineer at DocuSign after graduating from Metis.

• “I've started working much more on the data engineering side. When you work at a startup, you wear a lot of hats – you won’t just do data science work. Working at a startup forced me to do a lot more software engineering.” Read more.

Nadim became a Big Data Analytics Consultant after graduating from Brainstation. 

• “I work on our big data team, and technically, I’m developing Spark and Hadoop applications for clients like data ingestion pipelines, while also teaching the clients how to use them, what's actually happening in the back end, and creating documentation. For example, we help companies implement scalable big data infrastructures using Hadoop and Spark. On top of that, we’ll do reporting for companies – for example, building dashboard applications or mobile applications for a sales team.” Read more. 

Dwayne Jarrell was recruited by Facebook to become a Decision Scientist after graduating from General Assembly. 

• “I am a Decision Scientist, which is slightly different from the more typical “data scientist” role. Decision Science is specific to marketing analytics – I use similar tools and methods as data scientists, using them to evaluate marketing effectiveness and support Facebook’s marketing programs. There are at least a dozen scientists on our team. We sit in the Research department, called Insight and Analytics, so it includes marketing and research where we track all sorts of things.” Read more.

Read More:

• Are Data Science Bootcamps Worth It?

• Learn how you can use Natural Language Processing and Pandas on the job

• You don't have to become a Data Scientist – here are 5 reasons data skills are useful for everyone

• If you're not a math whiz, check out our webinar about all the math you need to learn for data science