Manager, Data Analytics

Lead analytics and clinical configuration strategy for our auto-decisioning platform, driving end-to-end solutions from data gathering through scaled deployment. Partner cross-functionally to translate business needs into analytical frameworks, independently recommending actions that shape product and business outcomes. Own auto-decisioning strategy for new client implementations with minimal oversight, while ensuring explainable, governance-aligned analytics practices. Build and mentor a high-performing team, embedding best practices for scalable, reusable analytics solutions. Ideal for a strategic thinker who thrives at the intersection of hands-on execution and team leadership in a fast-paced, data-driven environment.

- Provide thought leadership & strategic thinking to translate business problems into analytical and clinical configuration frameworks,and independently recommend actions and provide business insights

- Collaborate with cross-functional partners to understand their business needs, formulate and complete end-to-end analytic solutions that includes data gathering, analysis, ongoing scaled deliverables, and presentations

- Establish and maintain effective performance tracking; identify product and program improvement opportunities, form hypotheses, propose, design and implement tests to drive enhancement and optimization

- Foster a collaborative and innovative culture, set clear goals, mentor staff.

- Establish best practices and coach team members to develop and execute complex analytics initiatives with scalability and reusability in minds

- Develop, implement, and monitor day-to-day operations of analytics and clinical configuration team

- Execute analytics initiatives that directly impact our auto decisioning roadmap and business outcomes while working as part of a cross-functional team.

- Partner with Data Governance to ensure tractable and explainable analytics and responsible data

- Research, design, execute and optimize auto-decisioning strategy for new client implementations with minimal guidance and owning the end-to-end process

- Work with multiple types of healthcare data to build and maintain analytical and reporting solutions to support strategy and program decision making

- Identify optimization opportunities based on analyses to improve auto-decisioning performance and drive increased value for clients

- 1. Lead the analytics and clinical configuration team day-to-day — setting goals, mentoring staff, and coaching best practices for scalable, reusable analytics work.

- 2. Own the end-to-end auto-decisioning strategy for new client implementations, from research and design through execution and optimization, with minimal guidance.

- 3. Translate business problems into analytical and clinical configuration frameworks, build end-to-end analytic solutions (data gathering, analysis, scaled deliverables, presentations), and track performance to identify improvement opportunities.

ISMS roles and responsibilities( Manager Roles)

- Good knowledge of Information security

- 5+ years of hands on management experience in healthcare analytics

- 7+ years of experience in data science, analytics, and governance with at least 2 years of management experience hiring and developing teams

- Strong software development skills with proficiency in Python and SQL. Experienced user of data science libraries

- Proven track record in building and scaling data analytics teams, including recruitment, mentoring, and performance management.

- Ability to meaningfully present results of analyses in a clear and impactful manner. Able to break down sophisticated machine learning and data science model knowledge to digestible information for non-technical audiences.

- Expertise in translating complex business problems into end-to-end data products with a quantifiable business impact

- Advance degree (MS or Ph.D.) in a quantitative field, Statistics, Math, Economics, Engineering, Computer Science, Business Analytics, Data Science.

- Solid understanding and experience in machine learning algorithms, statistics, pattern recognition, classification, and data mining models.

- Comprehensive knowledge of the healthcare industry, products, systems, business strategies and products.

- Experience designing patient and provider analysis strategy and generate actionable insights from claims, emr and/ or lab data