Data Scientist

Bask Health; United States; On-site; USD 80,000 - 130,000; Full time

Job summary

A healthcare innovation company is seeking a Data Scientist to analyze data, generate insights, and influence product strategies. The ideal candidate will have a Bachelor's degree in a quantitative field and 3+ years of experience in data analysis or science. Responsibilities include designing prediction algorithms and collaborating with teams to enhance product development. Proficiency in Python, SQL, and data visualization tools is required. A passion for improving healthcare through data analytics will be essential.

Qualifications

• 3+ years of experience in data analysis or data science, influencing product decisions.
• Experience with cross-functional teams in healthcare or related industries.
• Ability to extract insights from complex datasets and apply machine learning.

Responsibilities

• Analyze raw data for quality and structure.
• Design and implement prediction algorithms.
• Collaborate with engineering for production-ready analytics.
• Generate insights for business improvements.

Skills

Data manipulation and analysis using Python

Data visualization tools

Statistical techniques

Analytical problem-solving

Excellent communication

Education

Bachelor’s degree in a quantitative field

Advanced degrees (Master’s or PhD)

Tools

Tableau

SQL

Alteryx

AWS

Google Cloud

Job description

At Bask Health, 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.

Responsibilities

• Analyze raw data: assessing quality, cleansing, structuring for downstream processing
• Design accurate and scalable prediction algorithms
• Collaborate with engineering team to bring analytical prototypes to production
• Generate actionable insights for business improvements

Qualifications

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.

Experience

• 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.

Technical Skills

• 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.

Analytical Skills

• 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.

Soft Skills

• 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.