Director, AI/ML & Data Science

Allied Benefit Systems•Chicago, IL

10h•Remote

About The Position

POSITION SUMMARY: The Director, AI/ML & Data Science will drive AI initiatives that deliver measurable value in the healthcare benefits domain. The Director will lead the development of predictive models and retrieval-augmented GenAI applications from concept through production integration, emphasizing reliability, reusability, and compliance in a regulated environment. They will manage a team and collaborate across product, engineering, and business units to ensure AI solutions achieve real-world impact. ESSENTIAL FUNCTIONS: Manage and mentor the data science team to build production-grade AI solutions that address key business needs. Focus on deploying models and ensuring each integration yields concrete business impact. Oversee full model integration with core systems in partnership with engineering. Establish robust MLOps pipelines for continuous deployment, data drift alarms, model operations monitoring, and models retraining You will implement A/B production tracks (i.e., sampling holdouts) ensuring continued measurement of your solutions’ benefits and design models for reuse across multiple applications and teams. In coordination with governance team members, ensure strong AI governance by following ISO 42001 standards and internal SOPs. Serve on the Model Review Board to evaluate new models and user-built AI tools, confirming they meet quality, ethical, and intended-use criteria before and after deployment. Work with technical product owners, engineering, finance, and business stakeholders to align data science projects with desired outcomes. Contribute to cost-benefit and ROI analyses for proposed AI initiatives, helping prioritize projects based on business value, feasibility and user-adoption. Communicate project updates and outcomes to business stakeholders and senior leadership in clear business terms. Evaluate emerging AI technologies and external solutions. Partner with vendors and assess commercial off-the-shelf AI tools to complement internal efforts, ensuring deployed solutions remain current and high performing. Collaborate with peers in AI Quality Assurance, ML Engineering Product, and AI Governance to develop a cohesive, high performing AI Team. Play active role in hiring and mentoring talent across these functions as the program grows. Lead, coach, motivate and develop. Responsible for one-on-one meetings, performance appraisals, growth opportunities and attracting new talent. Clearly communicate expectations , provide employees with the training, resources, and information needed to succeed. Actively engage, coach, counsel and provide timely, and constructive performance feedback.

Requirements

Bachelor’s degree in a quantitative field is required. A Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related discipline is strongly preferred.
12+ years in data science or advanced analytics, demonstrated sustained performance with impact at team(s) or department level..
At least 5 years at a manager level and successful demonstrated leadership competencies.
Proven track record of deploying machine learning models into production with operational maintenance.
Experience with PII/PHI in healthcare, insurance, or other regulated industries is required.
Deep knowledge of machine learning and statistical techniques (e.g., predictive modeling, NLP).
Hands-on proficiency with Python and core ML libraries (pandas, scikit-learn, TensorFlow/PyTorch) and data pipeline tools.
Able to guide the team on technical issues and review code or model designs.
Strong grasp of MLOps and software engineering practices.
Experience implementing model versioning, testing, continuous integration/deployment, and monitoring in a cloud environment (Azure preferred).
Familiarity with designing A/B tests or pilot programs to evaluate model performance and business impact over time.
Able to connect data science work to business KPIs and customer outcomes.
Experience contributing to ROI assessments or cost-benefit analyses of projects.
Solid understanding of data privacy, model risk management, and AI ethics in product development.
Excellent leadership and communication skills.
Proven ability to recruit and develop talent, foster an innovative yet execution-focused team culture, and coordinate efforts across disciplines.
Executive presence to present plans and results to senior leaders, translating complex technical topics into actionable insights for business audiences.

Responsibilities

Manage and mentor the data science team to build production-grade AI solutions that address key business needs.
Focus on deploying models and ensuring each integration yields concrete business impact.
Oversee full model integration with core systems in partnership with engineering.
Establish robust MLOps pipelines for continuous deployment, data drift alarms, model operations monitoring, and models retraining
Implement A/B production tracks (i.e., sampling holdouts) ensuring continued measurement of your solutions’ benefits and design models for reuse across multiple applications and teams.
In coordination with governance team members, ensure strong AI governance by following ISO 42001 standards and internal SOPs.
Serve on the Model Review Board to evaluate new models and user-built AI tools, confirming they meet quality, ethical, and intended-use criteria before and after deployment.
Work with technical product owners, engineering, finance, and business stakeholders to align data science projects with desired outcomes.
Contribute to cost-benefit and ROI analyses for proposed AI initiatives, helping prioritize projects based on business value, feasibility and user-adoption.
Communicate project updates and outcomes to business stakeholders and senior leadership in clear business terms.
Evaluate emerging AI technologies and external solutions.
Partner with vendors and assess commercial off-the-shelf AI tools to complement internal efforts, ensuring deployed solutions remain current and high performing.
Collaborate with peers in AI Quality Assurance, ML Engineering Product, and AI Governance to develop a cohesive, high performing AI Team.
Play active role in hiring and mentoring talent across these functions as the program grows.
Lead, coach, motivate and develop.
Responsible for one-on-one meetings, performance appraisals, growth opportunities and attracting new talent.
Clearly communicate expectations , provide employees with the training, resources, and information needed to succeed.
Actively engage, coach, counsel and provide timely, and constructive performance feedback.