Director, AI and Data Science (Remote)

Alignment Health

3d•$198,219 - $297,329•Remote

About The Position

Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most: the chronically ill and frail. It takes an entire team of passionate and caring people, united in our mission to put the senior first. We have built a team of talented and experienced people who are passionate about transforming the lives of the seniors we serve. In this fast-growing company, you will find ample room for growth and innovation alongside the Alignment Health community. Working at Alignment Health provides an opportunity to do work that really matters, not only changing lives but saving them. Together. The Director, AI and Data Science enables our enterprise AI strategy and oversees the development of scalable machine learning and artificial intelligence solutions that power next-generation care delivery models for seniors. This role is accountable for creating innovative data science solutions that deliver measurable business impact, differentiate the organization in the market, and accelerate top-line growth. The Director, AI and Data Science, combines deep technical expertise with strategic leadership to embed ML and AI capabilities into product design, business domains and continuously improving our data science fundamentals. And supports the company’s responsible use of AI that emphasizes our core values of Safety, Responsibility, Trust, Transparency, Fairness and Equity, and Empowerment.

Requirements

Minimum 7+ years professional work experience as a data scientist, engineer or developer of ML/AI solutions
5+ years of deep technical experience analyzing and modeling structured, semi-structured, and unstructured data using machine learning / predictive modeling
Record of delivering ML/AI projects in production environments
Demonstrated success in hiring great data scientists and growing junior team members through mentoring, collaboration, and coaching
Up-to-date knowledge of data science related technologies and data engineering best-practices
Demonstrated proficiency in SQL and relational databases. Solid data structures & algorithms background.
Expert knowledge of analytical platforms and tools used to build and deploy Machine Learning models
Excellent storytelling skills and the ability to present complex information simply in both small and large group settings to technical/non-technical audiences
Bachelor’s degree in Computer Science, Engineering, Statistics, or a related quantitative field

Nice To Haves

Experience in healthcare or other highly regulated industry
Experience with embedding approaches, vector databases, and RAG
Databricks/Spark Model Deployment
Advanced understanding of Python Software Development patterns and useful data science package
Planning and managing the software development lifecycle in GitHub (e.i, testing, feature planning, CI/CD, release schedules
Databricks/Spark model deployment
Advanced understanding of Python software development patterns and useful data science packages
Master’s or PhD in Computer Science, Engineering, Statistics, or a related quantitative field

Responsibilities

Model Development Develop and deploy scalable machine learning and AI solutions in production environments, ensuring performance and sustainability
Build and refine models for customer segmentation, risk prediction, clinical decision support, and other healthcare-specific use cases
Support cross-functional initiatives involving both traditional ML and emerging GenAI use cases
Statistical Rigor and Validation Ensure rigorous use of statistical methods, reproducibility, and documentation across all projects
Design and implement statistical tests, A/B experiments, and performance monitoring strategies
Evaluate ML/AI models and products for fairness in output, targeting and actions
Cross Functional Collaboration Partner with stakeholders to define problem statements, identify data sources, and design effective solutions
Build and maintain robust data pipelines, modeling workflows, and monitoring tools in collaboration with engineering and data platform teams
Partner with senior and executive leadership to define and advance the enterprise AI roadmap, identifying high-impact opportunities to embed ML and AI services into core business workflows
Team Development Lead multiple high-impact data science projects across areas including Clinical, STARs, Risk Adjustment, Claims, Pharmacy, Marketing and Member Experiences
Manage and mentor a team of data scientists; provide technical guidance via review of code, models, and analytical approaches; foster professional growth; and drive a culture of experimentation and continuous learning
Fulfill supervisory responsibilities in accordance with organization policies and applicable laws. Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance; rewarding and disciplining employees; and addressing complaints and resolving problems.