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# Associate Director, Enterprise Data Science

- **Company:** Alkermes, Inc.
- **Location:** Cambridge, MA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $160,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Application Frameworks, Business Software, Cloud Computing, Information Engineering, Data Governance, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, Salesforce.Com, SQL Databases, Workflow Management Systems, Enterprise Data Management, Feature Engineering, Snowflake, Generative AI, Build Management, Information Technology, Machine Learning Operations, Virtual Agents, Software Coding
- **Published:** August 1, 2026
- **Apply:** https://www.careerjet.com/job/us5a6ff4bc616472eec049b86ec65d6035/eaa

## About the Role

Master's degree in Data Science, Statistics, Computer Science, Applied Mathematics, Economics, Engineering, or a related quantitative field. Ph.D. preferred, 10+ years building and deploying advanced analytics, machine learning, and AI solutions that deliver measurable business impact.
Experience supporting Commercial Analytics use cases within pharmaceutical, biotechnology, or healthcare organizations strongly preferred.
Experience leading cross-functional AI and data science initiatives from problem framing through deployment and value realization.
Experience managing stakeholder relationships and influencing business decision-making at multiple organizational levels.
Technical Skills
Proficiency in production programming using Python and SQL.
Deep understanding of machine learning algorithms, statistical analysis techniques, predictive modeling methodologies, and end-to-end MLOps management.
Familiarity with cloud computing and ML platforms; AWS experience required and Snowflake experience preferred. Prior experience with use of AI tools in code development and management workflows is a plus.
Experience with data engineering, feature engineering, data governance, and scalable machine learning pipelines (dbt experience preferred).
Experience working with commercial data assets such as CRM, prescribing, claims, specialty pharmacy, patient services, or engagement data preferred.
Core Competencies
Proven ability to design and implement end-to-end AI and machine learning solutions from business problem definition through value realization.
Strong business acumen with the ability to connect technical solutions to commercial outcomes.
Strong problem-solving and analytical skills, with an aptitude for both technical innovation and stakeholder management.
Strong leadership and project management skills, with experience mentoring and developing technical talent.
Excellent communication and interpersonal skills with the ability to collaborate effectively across cross-functional teams and executive stakeholders.
Strong organizational skills, with demonstrated ability to manage multiple projects and competing priorities and ambiguities in a fast-paced environment.
Strong ownership mindset and accountability for outcomes.
Preferred Qualifications
Experience in pharmaceutical, biotechnology, or healthcare industries.
Direct experience supporting Commercial, Sales, Marketing, Market Access, Patient Services, or Field Force effectiveness initiatives.
Familiarity with Veeva CRM, IQVIA, claims, prescription, specialty pharmacy, and patient-level commercial datasets.
Familiarity with regulatory and compliance standards applicable to healthcare data (e.g., HIPAA).
Exposure to GenAI innovation, agentic AI systems, and advanced customer intelligence platforms.

## Description

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, thought partner, and mentor within the team. You will take ownership of key AI and machine learning initiatives 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 Commercial Analytics within the pharmaceutical industry; inquisitive data science skills; clear and compelling communication skills; an exceptional sense of ownership and accountability; and demonstrated success delivering machine learning products that create business value.
This role is based in our Waltham location and would work a hybrid office schedule.
Responsibilities:
Key Responsibilities
Support and Scale Data Science Use Cases
Develop and deploy complex analytical models and predictive insights to inform strategic decisions.
Implement data science solutions, including but not limited to predictive machine learning models, recommender systems, and agentic AI applications.
Lead development of commercial AI use cases including HCP targeting, customer suggestions, commercial opportunity identification, prescribing behavior prediction, and customer segmentation.
Scale proof-of-concept data science ideas and products into maintainable production software services; leverage best practices for production-ready code development and MLOps to build solutions that are stable, efficient, and scalable.
Partner with engineering teams to operationalize machine learning models and integrate outputs into business applications and digital workflows.
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 AI-driven products and analytics solutions.
Serve as a trusted advisor to stakeholders by helping them understand INDIGO's capabilities and translate business challenges into high-impact data science opportunities.
Facilitate structured discovery and problem-framing sessions to identify opportunities where AI, machine learning, automation, and advanced analytics can drive measurable business value.
Collaborate closely with commercial business leaders and domain experts to ensure models and solutions reflect real-world business processes and market dynamics.
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 user adoption, ensuring stakeholders understand, trust, and effectively integrate AI-driven recommendations 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 products, reusable frameworks, and scalable AI/ML platforms that drive commercial performance and establish consistent foundations for future AI applications.
Lead and manage high-impact data science initiatives across the organization, including scope, timelines, risks, and resource planning.
Drive the development of scalable machine learning capabilities that can support multiple brands and commercial use cases through reusable frameworks and automation.
Evangelize and contribute to scaled adoption of AI and machine learning capabilities across the organization.
Stay updated with advancements in data science, machine learning, and generative AI and evaluate emerging technologies for practical business application.
Track and communicate progress on data science initiatives while managing shifting priorities and business needs.
Champion FAIR principles and guide the organization in their application to ensure long-term data usability and accessibility.
Functional Ownership of Digital Products
Bring an end-to-end product lifecycle management mindset to INDIGO initiatives, with a clear focus on maximizing long-term business value.
Take ownership of Commercial AI and analytics products, ensuring reliability, scalability, business relevance, and ongoing stakeholder adoption.
Play a key role in shaping product and 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.


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