Forging a Career Path in Data Science From Beginner to Expert – ODSC Career Expo

Career Insights Conferences Featured Post Career Insights odsc eastposted by ODSC Team April 15, 2019 ODSC Team

Data Science, data engineering, and machine learning jobs continue to rank as some of the most sought after and highly paid...

Data Science, data engineering, and machine learning jobs continue to rank as some of the most sought after and highly paid jobs on the planet, according to Thinknum.

However, finding the right job is more important than ever. This may be a lucrative field, but many quickly find that landing your first or next data science gig is harder than expected.

Even already-established data scientists may have difficulty getting the higher-paying job they deserve, or the managerial position that they’re ready for. These more-advanced jobs also demand that you’re not just a good data scientist, but that you’re also well-rounded and versatile, and have plenty of soft skills to complement your technical knowledge. Let’s not forget that you need to be expanding on your knowledge of frameworks, models, languages, and so on.

Thus, anyone looking to enter or expand on their data science career path needs to have an actionable plan. This includes both your career path itself and the learning path you need to make you a stronger data scientist going forward.

The ODSC East 2019 Career Expo is more than a career fair. It’s an expo to help you explore your career path as well as your learning path.

What will I learn at the ODSC Career Expo?

Beyond networking with hundreds of other data science professionals, meeting hiring managers of household-name organizations, and working on your resume, there are a few talks that will help you learn more about careers in data science.

Chart Your Course: Finding Data Science Role That Sparks Joy: Brandon Rohrer, Data Scientist at Facebook and Instructor at End-to-End Machine Learning

In this session, we’ll take an aerial tour of data science’s major subfields and explore strategies for acquiring skills in each of them. Most importantly, we will talk about how to choose where to invest your limited study and development time. By the time we are done, you will have a better map of the data science territory and feel more comfortable charting a path that is both satisfying and professionally rewarding.

Balancing Life Today And Dreams For Tomorrow: Caitlin Peloquin, Financial Advisor at Ameriprise

In this talk with Caitlin Peloquin, Financial Advisor at Ameriprise, you will learn about a topic that isn’t discussed as much as it should be – work-life balance! She will cover everything from better understanding your (future) company’s benefits, factoring physical and financial health, and overall financial evaluation.

Transition Your Career To Data Science: David Borrelli, PhD, Data Science Program Director at Insight Data Science

What if you aren’t already a data scientist, and Google just isn’t cutting it for finding out the information you need to make that transition? Here, David will help you figure out your route to your first job in data scientist, whether you’re a student preparing for post-graduation plans, or someone already mid-career and looking for a change. He will help you define the target outcome by discussing the different flavors of data science roles that exist, and then work backwards and discuss the concrete things you can do to get to that goal.

Effective Communication is Key to Furthering Your Data Science Career: Kristen Kehrer, Founder of Data Moves Me, LLC

Clearly communicating complex material is what will differentiate you as a data scientist. In this talk, Kristen will cover models she’s built throughout her career, and how she could have more effectively communicated with her stakeholders to build trust and establish herself as a thought partner. Leveraging these communication skills, you will discuss how to tackle some of the most popular behavioral interview questions for data science positions.

How Competing In Data Mining competitions Makes You A Great Data Scientist! Claudia Perlich, PhD, Senior Data Scientist at Two Sigma

Over recent years, data mining competitions have gained a good amount of interest and attention. This might be partly due to seemingly lucrative prize money – 1 Million for the Netflix Prize and 3 Million for the Heritage Health Prize along with a good amount of stardom. In addition, companies increasingly use Kaggle as a hunting ground for talent extending job interviews to the highest ranking submissions. So, how can you use these platforms to showcase your skills and get your first data science job, or to prove you’re a master and get that next job?