Associate Director - Data Modeling

Job Title: Associate Director - Data Modeling

Location: Cambridge, MA

About the role

As an Associate Director - Data Modeling, you will provide Data Modelling subject-matter-expertise to ensure high-quality analysis-ready data assets are created and utilized in a systematic manner for insight generation within R&D.

How will you contribute:

Design, plan and implement data modelling activities, based on R&D portfolio and business priorities. Design projects, activities and generate data mapping and harmonization specifications within the Data Modelling capability area. Provide Subject-Matter-Expertise during the implementation of data mapping and harmonization specifications. AI-Ready Data, Data Curation Based on R&D needs and input from R&D organizations and functions, provide input for the identification of data assets and data sets for curation and other transformations to create AI and analytics ready data sets and assets. Assess, design and implement curation methodologies with input from the Data Org capability area team members and other SMEs. Accountable for the creation of data sets and assets that can be readily used for AI and advanced analytics use cases and in a consumable format for AI models. Work closely with the data science and analytics teams to ensure data models support and drive advanced analytics initiatives.

Primary and Secondary Data Architecture and Data Management

Design, specify and manage both primary and secondary data architecture and data management activities to ensure the efficient storage, flow and optimized use of data across the R&D organization.

Process Development and Optimization

Provide input for the assessment, design and implementation of data-focused processes that lead to optimized processes and workflows across R&D to increase operational efficiency, audit and inspection readiness and other R&D goals. Collaborate with R&D functions and organizations to assess and understand data and process-related gaps, pain-points etc. and provide input to create a goal state view. Design and optimize the data-centric components of these processes to move processes and workflows towards the goal-state. Collaborate with other process and workflow-related organizations within R&D and Takeda Enterprise organization to ensure that the goal-state processes, workflows etc. are holistic. Implement best practices for data processes and operations, ensuring standardized and streamlined workflows for data and insights generation across R&D. Collaborate with the other capability areas within the Data Organization to ensure that processes related to data strategy, governance, modelling and insight-generation are aligned and systematic.

Knowledge graph development

Based upon prioritized R&D needs and input from R&D organizations and functions, develop and implement knowledge graphs to support target identifications, indication expansion, pharmacology and other R&D use cases. Specify and document the knowledge models (foundational and subgraph). In collaboration with Data Governance team of the Data Org, develop the governance structure to guide the onboarding and governance of data sources from internal and external sources. Provide input for the operational activities needed to synchronize the data sources and knowledge database, including observability, quality, and recency of the data, so that the knowledge graphs stay current. In collaboration with the Insight and Analytics group team of the Data and Insights Org develop knowledge graph products with functionality related to user-interfaces, views, search, LLM-augmented RAG conversational interfaces and other gen-AI components to enable the dissemination of the knowledge and insights across R&D.

Data Model Development

Drive the assessment and development of data models based on R&D portfolio and business needs to enable informed decision-making across R&D. Provide input for the data model development life-cycle for existing data models or new data models that may need to be developed.

Leadership and Collaboration

Work with cross-functional teams, across R&D including the R&D DD&T Data Organization to ensure alignment and deliver impactful data solutions. Data Expertise: Strong background in data modeling, harmonization, and architecture design, with a focus on creating AI-ready data environments. Process Optimization: Ability to identify inefficiencies in data workflows and processes, designing and implementing solutions that enhance speed, accuracy, and usability. Advanced Analytics Enablement: Deep understanding of how data architecture and modelling supports AI, machine learning, and analytics, ensuring seamless integration and data flow. Strategic Leadership: Ability to align data modeling and process optimization with broader business objectives, providing guidance and vision to the data team. Cross-functional Collaboration: Lead efforts across R&D functions and organizations, to drive alignment between business and data teams to ensure success in implementing data strategies. Proven experience in data modeling across multiple R&D domains, data architecture (relational DBs, hierarchical DBs etc.) principles, data mapping and harmonization. Strong knowledge of AI-ready data processes, including data preparation, cleaning, curation, transformation and optimization for machine learning and AI applications. Good knowledge of data governance principles, quality, and compliance, ensuring that data models and processes align with regulated industry standards.

What you bring to Takeda

Minimum: Bachelor's degree in Computer Science, Data Science, Engineering, Information Technology, or a related field. Preferred: Master's degree in Data Science, Information Management, or a related field. Experience in data modeling, data architecture, and process optimization, with a focus on large-scale, complex data environments. 5-8 years of experience. Experience in AI-ready data preparation, data modeling for machine learning, and harmonizing data from multiple sources. Proven track record of leading data architecture and modeling initiatives, including the successful implementation of data processes and systems. Deep expertise in data modeling and data architecture. Strong background in AI and machine learning data preparation, including cleaning, transformation, and optimization. Good understanding of data governance, data management, and insight-generation principles. Working knowledge of cloud technologies (AWS, Azure, Google Cloud) and data platforms (data lakes, data warehouses). Excellent communication, presentation, and leadership skills, with the ability to engage stakeholders at all levels of the organization. Desired

Experience in the pharmaceutical, healthcare, or life sciences industries. Familiarity with data visualization tools (Tableau, Power BI) and data processing frameworks (Spark, Hadoop). Knowledge of regulatory data standards and experience with data privacy and compliance requirements.

Takeda Compensation and Benefits

Salary

Range: 154400.00 - 242550.00

The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local mini