Vice President Machine Learning

Remote Full-time
About the positionResponsibilities• Support the strategic vision for ML and related data science initiatives as we strive to analyze the patterns in member behavior most closely associated with effective outcomes to both drive outreach initiatives and inform internal training. • Lead a team of data scientists to ensure clear connection of their work to corporate goals, and set benchmarking standards to continuously evaluate progress against exploratory work tracks with the goal of effectively prioritizing precious team capacity against the most promising outcomes.• Work with both third-party and custom/in-house models to understand strengths and weaknesses of targeted investment in each (build vs buy), with the goal of balancing near-term progress vs long-term capability. • Work across teams, notably the Emerging Technologies Engineering function, to build the technical infrastructure needed to design, serve, deploy, and monitor our preferred long-term train/test/deploy process. • Evaluate and incorporate various sources of member engagement data (call transcripts, interaction history, user analytics, raw financial data, etc.) to produce the most complete possible picture of member population trends & opportunities.• Assist with member segmentation / persona development, and inform multiple operational functions including marketing, call center, digital experience and more. • Present often complex analytical insights to key stakeholders in a way that is easy to understand and actionable. Requirements• 10+ years of data science experience with a clear and demonstrated focus on healthcare population analytics using scalable analytical engines / machine learning models. • Graduate degree in a quantitative scientific discipline required.• Experience leading research functions and evaluating the likelihood of meaningful discovery vs allocation of resources. • Semantic analysis, NLP, or other experience with free text assessment required; when working with commercial models, deep understanding of prompt structures is preferred. • Demonstrable expertise with Python required; experience with common data science and ML libraries (PyTorch, Tensorflow, or similar, as well as standard libraries like Pandas, scikit-learn, etc.) is expected as part of your experience.• Proven experience in evaluation and application of existing analytic models/methods (trained models, research papers, etc.) to adjacent business use cases. • Demonstrable proficiency with relational and graph-based data models and query vocabulary (SQL, Cypher, etc.). • Proven experience with healthcare data and terminology/ontology standards (ex: FHIR, Snomed, etc.). • Experience in ML operations lifecycle and tools required for training, deployment, and testing loop of analytic models. • Prior experience with data visualization tools (e.g.Power BI, Cognos, Tableau, Looker) preferred. • Enjoys learning, dissecting, optimizing, and ultimately owning existing modelling methodologies. • Organized and methodical with very strong attention to detail. • Demonstrated ability to be adaptive and inquisitive; natural problem solver. • Ability to work autonomously with minimal direction on multiple endeavors at once. • Driven to deliver results with the ability to establish rapport, earn trust, and effectively collaborate with others. Nice-to-haves• Prior experience with data visualization tools (e.g.Power BI, Cognos, Tableau, Looker) preferred. Benefits• Family friendly benefits: Paid family and parental leave, fertility and family building benefits (including egg freezing, IVF, and adoption support), family care fund and Parents' Employee Resource Group. • Health, dental, vision and life insurance options for employees and family. • Free in-person, virtual and text-based mental health and wellness support. • Paid time off, including vacation, sick leave, personal days and summer flex time. • Company equity.• Bonus program. • 401(k) plan with company match. • Access to on-demand legal and financial advice. • Company social events. • Flex days (3 days a week in the office) and onsite meals and snacks for employees reporting into our NY office. Apply tot his job
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