About this role
PatientPoint operates a digital health network within physician offices to positively influence patient behaviors and health outcomes. The data science team addresses enterprise business challenges across provider growth, pricing, operations, marketing, campaign measurement, and customer attrition.
In this role, the senior data scientist advances algorithmic pricing by iteratively designing systems that evaluate supply, demand, willingness-to-pay, and expected ROI. The position involves building model interpretability, mentoring junior team members, and collaborating cross-functionally with engineering, product management, and pricing stakeholders.
Successful candidates bring extensive experience in data product development, statistical modeling, and optimization methods. An ideal practitioner is a self-directed critical thinker capable of translating complex analytical findings into actionable business narratives.
What you will do
- Advance algorithmic pricing across the business by iteratively designing systems that establish foundational signals of supply, demand, willingness-to-pay, and expected ROI.
- Build interpretability into pricing systems so quoted prices are explainable and price changes have clear drivers.
- Leverage machine learning, statistical modeling, and optimization methods to consistently deliver impactful results for clients.
- Mentor and coach less experienced data science team members as they continue to develop their skills.
- Collaborate closely with multiple teams including engineering, product management, and pricing.
- Promote models through the complete lifecycle and monitor ongoing model performance.
What you need
- Hold a Bachelor's degree in Applied Statistics, Computer Science, Economics, Operations Research, Business Analytics, Information Systems, or a related field.
- Bring 6 or more years of related data science experience developing data products, deploying models to production, and delivering analyses to stakeholders.
- Demonstrate fluency in Python and SQL with end-to-end data stack experience encompassing manipulation, analysis, visualization, model deployment, and pipeline orchestration.
- Possess advanced knowledge of machine learning and data science methods including predictive modeling, model validation, network analysis, price elasticity estimation, and optimization under constraints.
- Provide examples from previous experience or complete a project using analytics to create actionable insights.
Nice to have
- Master's or doctoral degree in Applied Statistics, Computer Science, Economics, Operations Research, Business Analytics, Information Systems, or a related field
- Professional experience in healthcare, pharmaceutical, value-based pricing, B2B pricing, and digital advertising industries
- Experience with Snowflake, Cursor, Airflow, HEX, and Gurobi
Benefits
- Competitive compensation
- Flexible time off to recharge
- Hybrid work options
- Mental and emotional wellness resources
- 401K plan
Skills and tech stack
Questions candidates ask
What is the location policy for this role?
This position offers remote work options within the US, with occasional travel up to 20 days per year.
What is the salary range for the role?
The base salary band is $143,374 to $210,544, with total compensation varying based on skills, qualifications, geographic location, and professional experience.
What tools and technologies are used?
The tech stack includes Python, SQL, Snowflake, Cursor, Airflow, HEX, and Gurobi.
What does the interview process involve?
Candidates will be asked to provide examples from their previous experience and or complete a project using analytics to create actionable insights.