Associate Director (Staff Data Scientist), Enterprise Data Science

Alkermes

2d•$158,000 - $180,000•Hybrid

About The Position

As an Associate Director within the INDIGO | AI Innovation Lab, you will lead the development and scaling of data science capabilities across the enterprise while acting as a technical expert and mentor within the team. You will take ownership of key projects and work closely with senior stakeholders to deliver data science-driven solutions that align with enterprise goals. This is a hands-on role where you will develop and implement cutting- edge data science solutions, build and maintain digital products, and enable the democratization of data through scalable tools and best practices. The ideal candidate will have a strong technical foundation in AI ‑ driven operations analytics across the pharmaceutical value chain - including supply chain, manufacturing, quality, EH&S, and business process excellence; inquisitive data science skills; clear and compelling communication skills; an exceptional sense of ownership and accountability; and experience in the pharmaceutical or health ‑ related industry. This role is based in our Waltham location and would work a hybrid weekly office schedule.

Requirements

Master’s degree in Data Science, Operations Research, Industrial Engineering, Computer Science, Statistics, or related field
10+ years building and deploying advanced analytics, operations research, or machine learning/AI solutions with measurable value impact
Experience solving Operations-focused problems (e.g., supply chain analytics, logistics optimization, manufacturing performance, inventory modeling) within pharmaceutical domain strongly preferred
Proficiency in production programming in languages such as Python and SQL. Comfort with foundational ML and AI libraries such as pandas, Numpy, scikit-learn, etc. is required.
Familiarity with cloud computing and ML platforms – AWS platform required; Snowflake experience preferred.
Strong knowledge of ML algorithms, LLMs, statistical analysis techniques, and end-to-end MLOps management.
Experience with data pipelines, data governance, and engineering best practices (DBT experience preferred).
Proven ability to design and implement high-quality end-to-end data science and GenAI solutions, from conceptualization and discovery through to tangible value delivery to the business
Strong problem solving and analytical skills, with an aptitude for technical and stakeholder management innovation
Strong leadership and project management skills, with experience mentoring junior data scientists
Excellent communication and interpersonal skills to collaborate effectively across cross-functional teams and get buy-in from stakeholders with a wide spectrum of technical proficiency
Strong organizational skills, with experience managing multiple projects and competing priorities and ambiguities in a fast-paced environment

Nice To Haves

Ph.D. preferred
Experience with optimization tools (e.g., OR-Tools, Gurobi, Pyomo) is a strong plus.
Prior experience with use of AI tools in code development and management workflows is a plus.
Experience in pharmaceutical, biotech, or healthcare industries.
Familiarity with regulatory and compliance standards (e.g., HIPAA).
Exposure to GenAI innovation and simulation modeling.
Ability to work a weekly hybrid schedule in our Waltham office.

Responsibilities

Support and Scale Data Science Use Cases
Develop and deploy complex analytical models and insights to inform strategic decisions
Implement data science solutions, including but not limited to agentic AI applications and predictive ML models
Develop pilot operations planning and optimization use cases using established operations research methodologies, with a focus on validation, impact, and scalable deployment
Scale proof-of-concept data science ideas and products into maintainable production software services; Leverage best practices for production-ready code development and DevOps to build solutions that are stable, efficient, and scalable
Stakeholder Engagement and Collaboration
Act as a key partner to cross-functional teams, providing technical and strategic guidance in the design, development, and implementation of digital products, optimization tools, and AI-driven solutions
Serve as a trusted advisor to stakeholders helping them understand INDIGO’s capabilities and guiding them in translating complex business challenges into high ‑ impact data science use cases
Facilitate structured discovery and problem-framing sessions to identify root causes, uncover operational inefficiencies, and prioritize opportunities where AI/ML, optimization, or automation can drive measurable value
Collaborate closely with domain experts to ensure models and solutions reflect real-world constraints and operational realities
Influence decision-making through clear, actionable communication, synthesizing complex analytical results into insights that resonate with both technical and non ‑ technical audiences
Champion change management and adoption, ensuring stakeholders understand, trust, and effectively integrate new AI/ML tools into their workflows
Build long-term partnerships with business owners, fostering ongoing collaboration, feedback loops, and continuous improvement for products and models in production
Lead the Development of Data Science Capabilities
Design and build production ‑ grade digital tools, reusable frameworks, and scalable AI/ML platforms that drive operational performance and enterprise efficiency while establishing consistent, reusable foundations for all current and future AI applications
Lead and manage high-impact data science initiatives across the organization, including scope, timelines, and resource needs
Evangelize and contribute to scaled adoption of ML and AI capabilities across the organization
Stay updated with advancements in data science and integrate emerging technologies into solutions where applicable
Track and report progress on data science initiatives while accounting for shifting priorities and timelines to ensure alignment with strategic objectives
Champion FAIR principles and guide the organization in their application to ensure long-term data usability and accessibility
Functional Ownership of Digital Products
Bring end-to-end product lifecycle management mindset to INDIGO initiatives, with a clear focus on optimizing long-term value of developed products and capabilities
Take ownership of INDIGO products within the operations domain, ensuring products’ reliability, scalability, and continued business relevance.
Play a key role in shaping portfolio strategy by contributing expert judgment and nuanced thinking on the direction, growth, and integration of the products they own
Mentor and develop the talent supporting their product portfolio, fostering a collaborative and continuously learning team environment