What are the responsibilities and job description for the Product Data Scientist position at Bask Health?
Product Data Scientist at Bask Health
At Bask Health, Product Data Scientists are at the heart of our mission to revolutionize healthcare. They uncover key insights, shape product development, and influence a culture of data-informed (not data-driven) decision-making. By working cross-functionally, our data scientists help guide what we build and how we build it, ensuring our solutions deliver real-world impact.
Why You’ll Love Working at Bask Health- Discover actionable insights
Seek objective truths through analysis, challenging assumptions, and uncovering the stories hidden in the data to guide decision-making. - Drive meaningful change
Apply your analytical, statistical, and technical expertise to generate insights that directly influence our product decisions and business strategy. - Work with advanced tools
Utilize cutting-edge techniques like regression analysis, segmentation, and A/B testing to inform product optimization and continuous improvement.
Join us and play a pivotal role in shaping innovative solutions that transform telehealth, empower patients, and redefine the future of healthcare.
Educational Background- Bachelor’s degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Advanced degrees (e.g., Master’s or PhD) in relevant disciplines are a plus.
- 3 years of experience in data analysis, data science, or a related field, with a proven track record of influencing product decisions through data insights.
- Experience working with cross-functional teams, including product managers, engineers, and designers.
- Experience in healthcare, telehealth, or related industries is highly desirable but not mandatory.
- Experts in programming languages such as Python & SQL for data manipulation and analysis.
- Strong experience with data visualization tools (e.g., Tableau, Looker, or similar).
- Experience with Alteryx (1 Year)
- Proficiency in statistical techniques such as regression analysis, hypothesis testing, clustering, and segmentation.
- Experience with A/B testing and designing experiments.
- Familiarity with data tools (e.g., Segment, Snowflake), ETL tooling and cloud platforms (e.g., AWS, Google Cloud) is a bonus.
- Ability to extract actionable insights from complex datasets.
- Strong problem-solving skills and a keen sense of curiosity.
- Experience applying machine learning techniques is a plus.
- Excellent communication skills, with the ability to translate complex data into understandable insights for non-technical stakeholders.
- Strong project management skills, with the ability to prioritize tasks and meet deadlines.
- Collaborative and proactive mindset.