Enterprise Data Strategy and Sourcing Lead at MassMutual

Our ideal candidate is motivated by enabling business innovation, agility and growth at scale; demonstrates vision, skill and sound judgement leading large-scale, technology programs; and contributes business acumen, vendor management, enterprise data governance, and DevOps delivery insights.

Data, analytics and algorithmic decision making are at the core of MassMutual’s digital evolution. In this role you will be accountable to envision and establish an enterprise data strategy and sourcing service for critical data leveraged across business channels. You will create and maintain a strategic roadmap and delivery plan to stand up the capability; staff a team of researchers and data analysts; set internal SLAs for quality and availability; and exceed service expectations as you deliver fully-governed data and run this service like its own P/L. You will also be accountable to track team KPIs; coordinate intake and backlog management; support our agile initiatives; and ensure consistency of execution, quality and adherence to enterprise data governance. 

Objectives of the role

• Partner with business leaders and data scientists across business channels to understand their Client and Product strategy in order to anticipate and meet their data needs.
• Develop strategic services roadmap and vendor strategy which is aligned with the product/service strategy to democratize and maximize the value of data and analytics across the enterprise.
• Develop preferred list of data vendors which have the right balance of product/service capabilities and reasonable cost
• Increase business agility by centrally procuring and staging fully-governed data and strategically managing the data portfolio.
• Help the business optimize their spend by analyzing and eliminating unnecessary demand, executing competitive sourcing analysis, and vetting and utilizing higher-value/lower-cost alternatives.
• Identify, initiate, and project manage initiatives to successful completion that significantly reduce the expense base

Daily and Monthly Responsibilities

• Maintain a Data Strategy and Sourcing Roadmap that holistically addresses high-priority, high-value data needs across the enterprise.
• Drive and monitor program execution, scope and resource management, risk management, and a robust, multi-audience communications program to ensure transparency, efficient decision making, and predictable delivery.
• Establish and track quantitative measures of progress, value and risks aligned with our data and AI strategic imperatives. Produce regular status reports and dashboards.
• Collaborate and partner across the enterprise with leaders in data science, data architecture, data engineering teams, law, compliance, enterprise risk, and information security.
• Stand up the capability; staff a team of researchers and data analysts; set internal SLAs for quality and availability; and exceed service expectations as you deliver fully-governed data and run this service like its own P/L

Basic Qualifications

• Bachelor’s degree, in Science, Technology, Engineering or Mathematics (STEM) highly preferred
• Extensive experience with technology product ownership, and a successful track record establishing and executing complex, strategic, cross-functional service delivery programs. 
• Strong project management experience with preference for practical agile tactics and methodologies.
• Experience creating KPIs and using them to manage execution and inform strategy.
• Vendor management
• Excellent communication, problem solving, organizational and analytical skills.
• Able to work independently.
• Knowledge of data architectures, data modeling, business analytics, and DevOps software development life cycles/tool chains.
• Financial services knowledge, including core products, business processes and participants.

Preferred Qualifications

• Advanced degree preferred (M.S., M.B.A., and J.D.).

• Experience implementing and managing enterprise programs around data management and governance in highly regulated industries.
• Knowledge of methods in machine learning and artificial intelligence.
• Expertise with the following are considered a strong plus: financial industry regulations, GDPR, privacy impact assessments, statistical analysis, ML/AI development.