Data Scientist Spotlight: Michelle Muha

How does an optical engineer become a data scientist?

Through a passion for math and science. Michelle Muha started her career in the fiber optics industry after completing a degree in optical engineering at the University of California, Davis. Spurred on by that passion for math and science, she later moved into a research role in the solar industry and began taking online data science classes. Michelle then made the transition from process engineer to data scientist, focusing on statistical process control and analytics development. Michelle wanted to continue down the data science path and accepted a role as a data scientist with Sensor Tower about four years ago.   

What’s it like to be a data scientist at Sensor Tower?

Fun and supportive. When Michelle started at Sensor Tower the Data Science team consisted of Michelle, her manager, and one other person. Four years later she’s now a manager and there are 18 people in the department (and they’re hiring more)! Michelle has always felt there are never any questions that she couldn’t ask because Sensor Tower team members are always willing to help and openly communicate with each other. Even though Sensor Tower is a predominately remote organization, Michelle feels connected to her colleagues through their regular Slack communications and channels, GitHub and Zoom calls. She genuinely likes the people here! 

Sensor Tower colleagues are also very receptive to ideas (no ego here) as they’re trying to un-box elusive Apple and Google algorithms. It’s really fun to hypothesize and test what these two giant companies are doing and how they do it.  

What does your day-to-day look like?

Impactful! Michelle manages and prioritizes projects plans for the Store Intelligence product, which is focused on estimating download and revenue data for apps. Her team specializes in making products better by improving algorithms. She will also triage as challenges arise, coach and collaborate with team members on techniques and methods to move the product forward.

Because Sensor Tower is a mid-size company that continues to grow, Michelle’s team still has a lot of impact due to the lack of “red tape”. Things can move quickly giving her team the ability to pivot and evolve based on the needs of Sensor Tower’s customers.

Part of her team’s success is due to the collaboration with Sensor Tower’s engineering and product departments. Michelle’s team often works closely with engineering to improve data fetching and learn programming best practices. Michelle’s team also works with the product department on brainstorming new products to meet customer needs. They talk through items like what data is needed, if the product is feasible, and how well would the proposed product work.  

Are there career growth opportunities in Data Science at Sensor Tower?

Absolutely! As the company grows the career opportunities also grow. After a couple of years in her Data Scientist role, Michelle was offered leadership opportunities such as mentoring others and having ownership over complicated projects. Nine months later she was promoted into a manager role. Department leadership continues to define additional growth opportunities with the growth of the department and the company.

What kind of skills and background does Michelle look for when she’s hiring?

Data Science applicants should have both software engineering and analytics skills. There is no road map on how to estimate this stuff, so creativity and the ability to brainstorm where to find signals. A collaborative nature and a willingness to pitch in and help others.  And a strong ability to communicate: One should have the ability to discern complicated algorithms and explain them to someone who may not understand it. Part of the interview process includes a paired coding exercise. Michelle finds that this allows candidates to display their ability to be flexible, how well they work with others on ideas and if they are open to new ideas and can absorb information and incorporate it.  

If you’re interested in working with Michelle and others like her, check out our Data Science opportunities and apply today.