Director, Data and Analytics

Takeda Pharmaceutical CompanyCambridge, MA
3d

About The Position

The Director Digital Insights and Analytics is responsible for leading a team that performs complex data research and analysis to support business operations. This role involves creating data mining architectures, statistical reporting, and data analysis methodologies to identify trends in large data sets. By applying knowledge of existing and emerging data science principles, this role informs business decisions and contributes to Takeda's mission. OBJECTIVES/PURPOSE Lead Plasma Dervied Therapies (PDT) Data Strategy, Advanced Analytics, and Insights function, ensuring that the application of advanced analytics, AI/ML including generative AI (GenAI, Agentic AI) drives business value through impactful insights and data-driven solutions. Oversee the complete lifecycle management of advanced analytics products, from ideation and development through to deployment and performance optimization advancing the organization capbility maturity by bringing analytics to the center of the business operations Develop and execute strategies for transforming large volumes of data into actionable insights using cutting-edge AI techniques and quantitative methods to solve complex business problems. Guide teams to shape business strategy through innovative descriptive, predictive, prescriptive analytics and decision making solutions while ensuring cohesive, actionable insights that align with broader organizational objectives.

Requirements

  • Minimum: Bachelor's degree in Computer Science, Data Science, Engineering, Information Technology, Mathematics, or a related field.
  • Strong background in advanced analytics, data visualization and analytic solutions including dimensional data model, 10 years of experience.
  • Experience in modern analytics tools, technologies, and frameworks including cloud-based platforms, AWS techologies, AI/ML frameworks, serverless computing, data lake, datamart, etc.
  • Experience in data modeling, data architecture, and process optimization, with a focus on large-scale, complex data environments.
  • 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.
  • Essential: Deep expertise in data modeling and data architecture.
  • Strong background in AI and machine learning data preparation, including cleaning, transformation, and optimization.
  • Demonstrate Business Intelligence thought leadership, new and innovative ways to use data
  • Passionate about new technologies and innovation and embrace changes.
  • 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.
  • Ability to communicate complex technical concepts to non-technical business leaders.
  • Excellent written and oral communication skills.
  • Leadership and global team management skills with a focus on mentorship and talent development.
  • Strong desire to learn and experiment with new concepts.

Nice To Haves

  • Preferred: Master's degree in Data Science, Information Management, Engineering, Mathematics or a related field.
  • Experience in the pharmaceutical, healthcare, or life sciences industries.
  • Familiarity with regulatory frameworks and data privacy laws related to AI/ML applications (e.g., HIPAA, GDPR).
  • Knowledge of emerging AI technologies and trends in generative AI.

Responsibilities

  • Insight Generation and Analytics Lead the PDT Data and Analytics team centered on providing actionable insight and aiding PDT SBU in business decision-making. Own all aspects of delivering analytics solutions for the business. This includes but not limited to descriptive/diagnostic/predictive/prescriptive analytics, and decision support solutions in order to influence and grow business intelligence practice. Utilize machine learning, AI including GenAI methodologies to uncover trends, predict outcomes, and optimize business processes. Build PDT data acquisition and business intelligence strategies supporting multiple operating models include self-service and full-service analytics.
  • Data Strategy and Stakeholder Collaboration Obsess over our challenges and draw on creative thinking skills and collaborative nature to develop tangible data solutions with measurable business values. Regularly update the data strategy based on external insights, ensuring the organization remains competitive and innovative. Build strong relationships with key stakeholders across business units, ensuring that analytics projects align with business priorities and contribute to strategic goals. Collaborate with Data, Digital, and Technology (DDT), Privacy Office, and other related teams to ensure adherence to established analtyics solution standards, data security, and protocol algining with the Enterprise roadmap.| Oversee and manage multiple parallel projects, risk identifications/mitigations, prioritization, and cost control.
  • Product and Analytic Method Lifye Cycle Management Oversee the end-to-end lifecycle of analytics products, ensuring they are developed, deployed, and optimized for ongoing business use. Manage systems integration, Data Pipelines, and Data Ops specific to business requirements (real-time and batch, push & pull) & related governance, security, integrity & consistency in order to support both Operational and Analytic use cases Coordinate with team members in Analytics, Data Science, and Technology to indentify best practices and procedures for data usage and data demorcratization Continuously monitor the performance and effectiveness of data science products and analytics models, implementing improvements as needed. Ensure that the quality of data, reports, analytics and dashboards are maintained to support critical business decision
  • Innovation and Thought Leadership Lead the exploration and integration of emerging technologies and methodologies in data science, including generative AI and other cutting-edge advancements. Act as a thought leader in the organization by championing data science and analytics initiatives and promoting the value of AI-driven insights in strategic decision-making. Stay abreast of developments in AI, machine learning, and advanced analytics, ensuring the organization is adopting the best tools and methodologies available. Partner with technology leaders to drive the development of advanced analytic products through rapid prototyping and iterative design, enhancing analytical capabilities and product offerings.
  • Team Leadership and Development Recruit, lead, mentor, and develop a high-performing global team of data scientists, analysts, and engineers, fostering a culture of innovation, collaboration, and continuous learning. Ensure that the team has the necessary tools, skills, and resources to succeed in delivering impactful analytics solutions. Foster a collaborative environment that encourages creative problem-solving and the sharing of best practices across the data science team.

Benefits

  • U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others.
  • U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service