Senior Data Scientist - Operations

1w1 week ago

Function Health

CA · Full-time · $200,000 – $280,000

About this role

Function Health is the AI operating system for health, designed to empower people to live 100 healthy years. We are hiring a Senior Data Scientist, Operations to build the analytical and modeling foundation for Member Experience (CX) and Contact Center operations. This role unifies data across customer support, product, health, and business systems.

Develop models and metrics to understand members, improve experiences, boost efficiency, and enable proactive decisions. Perform analyses on member support and health testing data to prioritize initiatives. Create heuristic, predictive, or ML models like customer support demand forecasting.

This role suits those energized by fast-paced, high-growth environments and motivated by Function's mission. We foster a collaborative, dynamic setting to build the future of health. Join world-class talent with a bias toward action and growth mindset.

Function is venture-backed by Andreessen Horowitz, recognized by Fast Company’s Most Innovative Companies of 2024, and raised $298M Series B. Scale People systems, data, and insights to attract exceptional talent. Make real impact on global health.

Requirements

Degree in Data Science, Biostatistics, Computer Science, or a related quantitative field
5+ years of experience in data science or analytics at consumer or enterprise tech companies
Proficiency in Python, SQL, and data visualization tools
Experience at the intersection of data science, customer support operations, product data, forecasting, and workforce planning
Ability to develop models for operational efficiency and member insights

Responsibilities

Develop measurement frameworks, north star metrics, and data structures to facilitate decision-making across the company
Perform strategic and operational analyses to identify and prioritize product and business initiatives, such as insights from member support and health testing data
Develop heuristic, predictive, or ML models and data products to empower the business, e.g., customer support demand forecasting
Unify data across customer support, product, health, and business systems
Drive self-service through documentation, education, and training to enable a data-driven organization
Ensure data quality, security, and compliance within all analytical frameworks