Senior Manager, Machine Learning Engineering

At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.

As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day.

Position Summary

Our Insights Engine team within the Analytics & Behavior Change (A&BC) division of our Data, Digital, Analytics, Technology (DDAT) organization is seeking a Senior Manager, ML Engineering.  We are looking for passionate, driven individuals who are ready to lead a team of analytics engineers (AI, ML, software, data) who support A&BC's Insights Engine team.  Our work puts actionable insights into the hands of clinical activation channels who are working to identify potential conditions. 

This leadership role has a broad technical portfolio of data, analytics, software and machine learning assets that ensure our network teams are armed with the competitive intelligence they need to ensure the health of Aetna’s network and contracts.  As the healthcare landscape evolves and changes, our team’s work is a crucial part of the overall CVS Health mission: transforming care to drive superior health outcomes and a seamless patient and consumer experience.

As a Senior Manager, you will be responsible for guiding a team as they build best-in-class applications that integrate advanced analytics capabilities (predictive models, LLMs, vector search) into applications and data products built within the Google Cloud Platform.  You will develop the strategies and tactics that we use on the path to delivering cutting-edge products, leveraging your expertise in engineering management, software architecture, and agile development lifecycles.  As you join a high-caliber group of engineering leaders dedicated to delivering impact quickly while ensuring our technical assets and architecture are constantly maturing, your experience, instincts, and insights will enable us to iterate quickly while we explore bold technical solutions to complex problems.  You encourage the team and champion the delivery of the right software at the right time, ensuring that we maximize our impact.

Responsibilities:

• Technical oversight: Technical leader capable of designing and overseeing the build-out and operations of complex distributed systems at scale in a fast-paced analytics organization
• Engineering leadership: Able to technically direct, support, and evaluate data, software, and ML engineers and their work product, ensuring we are building best-in-class solutions that can scale to meet our future non-functional requirements
• System performance: Monitor and optimize both team & system performance, identifying opportunities for enhancement and addressing any issues or bottlenecks.  Establish KPIs and OKRs that unlock quantitative insight so we can change processes with confidence.
• Talent management: Recruit, manage, mentor, and retain a high-performing engineering team while contributing to a positive and supportive culture, encouraging innovation, and driving a pragmatic balance of continuous improvement and effective value delivery.
• End-to-end ownership: Lead a team from strategy through delivery in complex and highly visible engineering projects.
• Prioritization and pivots: Guides team’s work prioritization in alignment with our strategic objectives. Coach an implementation team through pivoting as needed while remaining steadfastly focused on the overall objective. 
• Cross-functional collaboration: Collaborate closely with other technical teams (engineering, platform, infrastructure, security, governance) to understand their expectations and develop solutions in accordance with appropriate guidelines. 
• Coalition building: Establish effective relationships with partners and customers, ensuring that you understand their vision and can help them deliver their goals.
• Risk management: Proactively identify, communicate, and mitigate both internal and external risks.  Communicate clearly on progress, challenges, and opportunities to senior management and stakeholders, including presenting technical concepts to non-technical audiences. 
• The big picture: Understand how data, data science, and AI/ML can drive clinical and healthcare delivery strategies.  Build partnerships that enable business innovation through data and analytics.
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