Data and Analytics Specialist IV

Data and Analytics Specialist IV
Cambridge, MA (Hybrid)
06 months
Hybrid Role : 3 days onsite in Cambridge
Duration 6 months
We are looking for an experienced Data Architect with a strong foundation in data architecture, a clear understanding of how AI tools consume and interpret data, and hands-on experience with platforms like Tellius. This role sits at the intersection of data governance, AI enablement, and technical oversight, ensuring that enterprise data used in AI and analytics solutions is well-modeled, well-governed, and responsibly applied.
The ideal candidate understands both the technical side of data and the importance of governance, with experience working on RAG or other GenAI projects. They will work closely with Brand Data Leads, Data engineers, and Analytics teams to help decide how data is organized, controlled, and used in AI-powered tools and products.
Responsibilities
• Work closely with AI platform teams to understand their data needs, what data is being sent to their systems, and how it is processed and used.
• Design and oversee enterprise data architectures that support analytics, AI, and GenAI solutions, ensuring structures are scalable, secure, and aligned with governance policies.
• Set governance rules and access controls for data flowing into AI and analytics tools, ensuring it is shared responsibly and in compliance with standards.
• Map and monitor data flows into AI and analytics platforms, tracking transformations, lineage, and downstream usage.
• Develop and maintain data models, semantic layers, and metadata to ensure information is accurate, consistent, and business-ready.
• Collaborate with engineers, architects, and vendor teams to embed governance checks and quality controls directly into data pipelines.
• Review and approve new data integrations, ensuring they meet both architectural best practices and governance requirements.
• Ensure AI data readiness, confirming that data quality, structure, and compliance requirements are met before it is used for model training or inference
Qualifications
• Bachelor's degree with 7+ years of experience preferably in the pharmaceutical, biotech, or life sciences sector.
• Experience in both data governance and data architecture, with a track record of designing and managing enterprise data solutions.
• Strong understanding of how to build and maintain data models, semantic layers, and metadata, along with the ability to track data lineage.
• Hands-on experience working with AI or advanced analytics platforms, preferably Tellius, understanding how data flows into these systems and is used
• Ability to define and enforce governance rules, access controls, and compliance measures for data usage.
• Strong understanding of data pipelines, transformations, and integration design.
• Excellent collaboration skills with the ability to work effectively across engineering, architecture, product, and business teams.
• Familiarity with AI/GenAI concepts such as model inputs, training data preparation, and responsible AI practices.
• Experience in AI data readiness assessments, including data quality and compliance reviews.
• Knowledge of data privacy regulations and how they apply to AI and analytics use cases.
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