How to Become A Data Scientist

Sep 14, 2021 · St. Louis, United States of America

How to Become A Data Scientist

Dan London & Jonas Malave

Data science has become ubiquitous and indispensable as companies leverage their data assets to make better decisions, automate and optimize critical business processes, and create innovative and sophisticated products.

This exponential shift toward data science has led to a huge demand for skilled data scientists who can understand business needs, harness data, and construct statistical models to solve problems and drive improvements in business processes and customer experience.

In reality, however, these data scientist “unicorns” are largely mythical creatures. This is disappointing for hiring managers - but it should be comforting for those of us interested in a data science career but worried that we may not have the experience, education or expertise that ticks every box.

Have you considered getting into the field of data science, but feel uncertain about (a) what the field encompasses, (b) what data scientists actually do, (c) how someone “becomes” a data scientist or (d) which functional and technical skills are most prized by employers looking for potential candidates?

We are here to clarify that confusion and provide a sense of what makes a great data scientist job candidate (and, in turn, what makes a great data scientist).

This presentation will walk you through:
Introduction and comparisons of Data Science and other data-related roles to help clarify what Data Science is and what it is not
How to position yourself as a data scientist job applicant
Q&A / simulation session of a data science interview

Dan London is a Principal Data Scientist at Charter Communications. A former attorney, Dan’s data science career started by accident while he was working as a functional Business Analyst at the Nielsen Company. He was staffed on a small project team with a Statistician and an ETL developer; within weeks of the project launch both colleagues left the company and Dan was forced to fill all three roles. In his decade at Charter, Dan has helped develop machine learning models that identify drivers of internet service issues, predict the likelihood of sales completion vs. cancellation, and isolate customer segments for which self-installation may not be appropriate.

Jonas Malave Campos is an Associate Consultant for the Data & Analytics practice at Slalom. Jonas has been involved in Business Intelligence projects as a Data Analyst and Business Analyst in the development of Reference Data Management (RDM) and the improvement of current state reporting for a Fortune 100 company.

Jonas holds an M.S. in Computer Management Information Systems with a specialization in Business Analytics from Southern Illinois University Edwardsville and a B.S. in International Business from Lindenwood University. He is a LaunchCode/CoderGirl graduate of the Data Science track, and he is passionate about how data can enable better opportunities and business decisions in general.

Our event will start with 30 minutes of networking in zoom breakout rooms. We will then have a 45-60 minute lecture followed by 15 minutes of questions. Attendees are welcome to stay after and chat.

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