BNM-Senior Manager, Data Science & Analytics

Position: BN31M2-Senior Manager, Data Science & Analytics

BN31M2-Senior Manager, Data Science & Analytics

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Position Summary

The Senior Manager, Data Science & Analytics will lead strategic data science initiatives across multiple business units while managing a larger, more complex portfolio of advanced analytical projects. They will oversee data science teams, drive cross‑functional collaboration at the senior leadership level, and establish best practices for scaling data science capabilities across CAS. This role requires proven expertise in managing complex, enterprise‑level programs while enabling and empowering technical teams to deliver breakthrough AI/ML applications for scientific discovery.

Job

Accountabilities Strategic Program Leadership

• Team Oversight:
  Lead and coordinate a team of data science professionals working across multiple business verticals, ensuring alignment with enterprise objectives.
• Cross‑Functional Strategy:
  Partner with senior‑level stakeholders across Product, Technology, Content Operations, and other teams to define and execute data‑driven strategic initiatives.
• Portfolio Management:
  Oversee complex portfolio of concurrent high‑impact projects, optimizing resource allocation and ensuring delivery excellence.
• Best Practices Development:
  Establish enterprise‑wide standards for data science project management, delivery methodologies, and operational excellence.

Technical Program Management & Enablement

• Technical Vision Translation:
  Partner with senior technical leaders to translate business requirements into actionable technical strategies and roadmaps.
• Resource Optimization:
  Ensure teams have appropriate technical resources, tools, and infrastructure to deliver cutting‑edge AI/ML solutions.
• Innovation Facilitation:
  Create environments that foster technical innovation, enabling teams to explore advanced technologies including LLMs, multimodal AI, and automated scientific discovery workflows.
• Quality & Delivery Assurance:
  Establish rigorous project management frameworks ensuring technical deliverables meet business requirements and quality standards.

Organizational Development & Talent Management

• Team Building:
  Recruit, develop, and retain data science talent in partnership with technical leads; build succession planning for key roles.
• Leadership Development:
  Mentor and develop early‑career managers and senior individual contributors, focusing on both technical growth and leadership capabilities.
• Performance Management:
  Establish performance metrics, career development frameworks, and recognition programs for large, distributed technical teams.
• Culture Development:
  Foster a collaborative, innovative culture that attracts top‑tier technical talent and drives excellence through effective leadership and team dynamics.

Business Partnership & Strategic Impact

• Strategic Consulting:
  Serve as senior advisor to business leaders on analytical opportunities, translating complex technical capabilities into business value.
• Value Delivery:
  Drive measurable business outcomes with accountability for significant revenue impact and operational improvements through effective program management.
• Stakeholder Management:
  Build and maintain high‑trust, influential relationships with senior internal stakeholders and key external partners, serving as primary business interface for technical initiatives.
• Business Case Development:
  Develop compelling business cases for major data science investments, and present to senior leaders to inform critical business decisions.

Qualifications

• Master's Degree required in business, engineering, or quantitative discipline.
• Technical background preferred but not required (Statistics, Computer Science, Applied Mathematics, Data Science, etc.).
• 15+ years progressive experience in business leadership, technical team management, or other related roles.
• Proven track record leading enterprise‑scale initiatives with measurable business impact.
• Experience working closely with data science, engineering, or technical teams (direct technical experience preferred but not required).
• Experience in scientific/pharmaceutical/chemical industries preferred.
• Demonstrated…