Associate Director, Workplace/FM Data Science Manager

MSD•Rahway, NJ

15h•Hybrid

About The Position

The GWES Delivery team, part of the GSMG/GWES DS&I organization, is dedicated to supporting Workplace Services and Facilities Management through advanced analytics, insights, and data-driven decision making. This team collaborates closely with key GWES functions including Facilities Management operations, Integrated Facilities Management (IFM), Real Estate, finance, Workplace Experience & Smart Buildings, Asset management, and sustainability. The role of Workplace/FM Data Science Manager involves leading the development of analytics solutions to deliver actionable insights and improve operational and business outcomes across the global workplace and facilities portfolio. Reporting to the Director, Data & Analytics – GWES, this position requires close collaboration with GWES directors, regional leaders, and executive stakeholders to address complex business challenges by designing appropriate analytical approaches and models. It is a hands-on leadership role, demanding strong expertise in extracting scientific and business value from various data sources (operational, financial, sensor/IoT, service provider, RE data) using advanced analytics techniques such as statistical modeling, optimization, simulation, and machine learning.

Requirements

Bachelor Degree required.
Minimum of 5 years of relevant delivery of complex analytical projects (industrialized, validated), across data & analytics, digital platforms, or enterprise systems.
Demonstrated experience taking AI or advanced analytics use cases from prototype to production.
Strong background in data & analytics solutions for operational domains.
Solid software engineering foundation (Python preferred) and API‑based system integration.
Hands‑on experience designing and delivering Generative AI solutions (beyond PoCs).
Practical knowledge of Large Language Models (LLMs) and Experience integrating GenAI with Data lakes, analytics platforms, and enterprise systems, unstructured data sources.
Familiarity with cloud‑based architectures (Azure, AWS, or equivalent).
Working knowledge of LLMOps / MLOps concepts.
Practical understanding of AI Governance, Security & Enterprise Readiness.
Self-motivation, proactivity and ability to work independently with minimum direction.
Proven knowledge of business processes and industry/market trends within the pharmaceutical space.
Excellent business acumen, with proven ability to understand business processes in detail – both at global and region/country levels – and translate these into user stories and detailed business requirements.
Proven leadership and negotiation skills, along with good analytical and problem-solving skills.
Excellent interpersonal and communication skills (English – both oral and written), along with the ability to communicate appropriately and confidently with colleagues from different backgrounds and seniority levels.
Excellent organizational skills, with ability to navigate a complex matrix environment and organize/prioritize work efficiently and effectively.
Animal Vaccination
Business Intelligence (BI)
Business Processes
Business Process Modeling
Business Strategies
Communication
Computer Science
Data Analytics
Database Design
Data Engineering
Data Integration
Data Modeling
Data Science
Data Visualization
Machine Learning (ML)
Market Trends
Operational Excellence
Real Estate
Smart Buildings
Software Development
Stakeholder Relationship Management
Waterfall Model

Nice To Haves

Advanced degree in data science, mathematics, statistics, or computer science or related fields preferred.
Experience with Workplace strategy, Facilities management or Real estate business is a plus and desirable.

Responsibilities

Develop a deep understanding of GWES stakeholder needs and priorities (Workplace Services, Facilities Management, Real Estate, IFM, Smart Buildings, Sustainability …) and translate them into scalable analytics solutions aligned with business objectives.
Establish and maintain strong partnerships with global, regional, and site-level stakeholders, acting as a trusted analytics advisor.
Lead the definition and delivery of complex analytics initiatives, working closely with GWES business and IT teams to select the right analytical methodologies and data approaches.
Provide periodic performance and insight reporting to GWES Leadership, Regional Leads, Site leads and Service Owners as required.
Act as functional lead for a team of Business Performance Analysts and Data Analysts supporting GWES initiatives.
Maintain awareness of data science and analytics market trends, particularly as they apply to workplace services, facilities operations, Real Estate, IoT/smart buildings, and service performance analytics, and proactively identify opportunities to increase value.
Manage and develop a team of 1-2 data scientists, ensuring high-quality delivery, continuous skill development, and career growth within our Company.
Build and nurture a community of practice for advanced analytics within GWES/GSMG, mentoring junior colleagues and contributing to a strong, scalable analytics capability.
Contribute to innovation and experimentation, including ideation, proof-of-concepts, pilots, and measurable value realization.
Communicate analytics insights clearly and effectively to business audiences, helping drive organizational adoption of data-driven decision making, and supporting the evolution from descriptive to predictive and prescriptive analytics.
Promote a culture where analytics, modeling, and data are recognized as key differentiators for operational excellence and employee experience.
Support the GWES Data & Analytics Lead in developing standardized performance reporting, dashboards, and insights for leadership and operational reviews as needed.
Collaborate on performance management frameworks, including KPI definition, SLA monitoring, and continuous improvement initiatives.
Anticipate future analytics demands related to people, technology, budget, and business strategy, and design scalable solutions to support evolving GWES priorities.
Travel will be required (~15%).