Senior Product Data Scientist

At MyFitnessPal, we believe health starts with what you eat. Our mission is to create products that not only delight our users but also foster long-term engagement and loyalty.

We are seeking a talented Senior Product Data Scientist to join our team and help drive product improvements, analyze user behavior, and enhance user retention, which will be critical in shaping the future of our product. You will leverage your analytical skills to interpret complex data sets, understand user behaviors, identify trends, and provide actionable insights that will inform product development and marketing strategies. Your work will directly impact how users interact with our products, helping to increase user satisfaction and loyalty.

Technologies and languages we work with include: AWS, Airflow, Snowflake, Databricks, SQL, Scala, Python, SQL, Amplitude, Branch, braze, Tableau. We care more about your general statistical modeling skill than your knowledge of a specific language and or framework.

What you’ll be doing:

• Perform large-scale hypothesis testing and statistical analysis to find insights in complex analyses including:

  • Customer segmentation, clustering and lifecycle analysis

  • New business opportunity analysis and modeling, particularly for new product features

  • Predictive modeling to forecast user growth and product adoption

  • Dynamic pricing optimization

  • Predictive churn & retention modeling

  • Predictive behavior modeling for customer health success

  • Metric sensitivity analyses to identify leading indicators

• Partner with product leadership to solve business problems and identify trends for growth opportunities (i.e. suggest new analyses, experiments, user cohorts)

• Most importantly, be a trusted partner to our product managers and help them succeed in their mission to improve our product

• Live our core values in all you do:

  • Be Kind and Care

  • Live Good Health

  • Be Data-Inspired

  • Champion Change

  • Leave it Better than You Found It

  • Make It Happen

Qualifications to be successful in this role:

• MS in Computer Science, Data Science or other quantitative disciplines OR additional 2+ years of relevant experience

• 4-6 years of industry experience with machine learning and 3 years of experience supporting digital consumer products (preference given to subscription products)

• Experience with supervised and unsupervised learning algorithms (e.g., decision trees, random forests, clustering) 

• Proficiency in Python, R, or other data analysis languages 

• Ability to apply data science to real-world problems, capable of breaking down complex problems into key components where data science and AI can be utilized

• In-depth knowledge of Statistics/Probability/Machine learning

• Ability to provide written and oral interpretation of highly specialized terms and data, and ability to present this data to others with different levels of expertise

• Curious Mindset - We are looking for someone who enjoys seeking the truth through data - if you ever found yourself bringing in out-of-the-box datasets and theories because you just had to figure out why a number moved this is the job for you

• Travel Requirement: Approximately 10% travel will be required for this position

Please consider applying even if you don’t meet 100% of the qualifications. Research shows you can still be considered for a position if you meet some of the requirements. At MyFitnessPal, we’re building a fitness product for everyone and believe our team should reflect that. We encourage people of different backgrounds, experiences, abilities and perspectives to apply.

The reasonably estimated salary for this role at MyFitnessPal ranges from $140,000 - $170,000. Actual compensation is based on factors such as the candidate’s skills, qualifications, and experience. In addition, MyFitnessPal offers a wide range of comprehensive and inclusive employee benefits for this role including healthcare, parental planning, mental health benefits, annual performance bonus, a 401(k) plan and match, responsible time off, monthly wellness and technology allowances, and others.