Data Scientist, AI Engineering

Trinity Life Sciences • Barrington, RI

23h • $110,000 • Hybrid

About The Position

Trinity Life Sciences is a premier global commercialization partner to the life sciences industry, delivering evidence-based strategy, insights, and analytics to pharmaceutical, biotech, and medical device companies. With nearly 30 years of experience, Trinity serves over 300 clients, including 18 of the top 25 global biopharmaceutical companies, across every stage of the product lifecycle, from pre-launch strategy through post-market optimization. Recognized on Forbes' Best Management Consulting Firms list and ranked among the top health sciences consulting firms globally, Trinity combines human expertise with cutting-edge AI and data capabilities to help clients make decisions that ultimately improve patient outcomes. We are seeking a talented and analytically rigorous Data Scientist to join Trinity's growing Advanced Analytics practice. In this consultant-level role, you will partner with cross-functional teams and life sciences clients to design and deploy sophisticated data science solutions across commercial analytics, real-world evidence (RWE), patient analytics, and market access. You will work at the intersection of science, business strategy, and technology, translating complex data into actionable insights that drive commercialization decisions for some of the world's most transformative therapies.

Requirements

• Bachelor's or Master's degree in Data Science, Statistics, Biostatistics, Computer Science, Engineering, Mathematics, or a related quantitative discipline
• 3 to 6 years of professional experience in data science or advanced analytics, with at least 1 to 2 years in a consulting, professional services, or client-facing environment
• Strong proficiency in Python and/or R for data manipulation, statistical modeling, and machine learning; solid command of SQL for data extraction and transformation
• Demonstrated hands-on experience building and validating ML models (supervised and unsupervised) and deploying solutions in production or quasi-production environments
• Experience working with life sciences or healthcare data, including commercial datasets (claims, prescriptions, formulary) or clinical/real-world data (EHR, patient registries)
• Exceptional written and verbal communication skills; able to distill complex analytical findings into clear narratives and recommendations for executive, scientific, and commercial audiences alike, including the development of polished client deliverables such as PowerPoint presentations, analytical reports, and technical documentation, as well as confident facilitation of client workshops and steering committee meetings
• Proven ability to manage multiple project workstreams simultaneously, with strong attention to detail, analytical rigor, and a client-first mindset

Nice To Haves

• PhD a plus
• Familiarity with key commercial life sciences concepts: HCP/patient segmentation, field force effectiveness, market access, launch analytics, and KPI measurement
• Experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Databricks, Snowflake)
• Exposure to NLP, large language models (LLMs), or Generative AI techniques and their application in life sciences or healthcare contexts
• Working knowledge of data visualization platforms such as Tableau, Power BI, or custom dashboarding solutions
• Prior experience in a life sciences analytics consultancy or within the data/analytics function of a pharmaceutical or biotech company
• Publication record, conference presentations, or other demonstrated thought leadership in data science or health analytics

Responsibilities

• Design, develop, and deploy predictive and prescriptive models to address commercial challenges such as patient identification, HCP targeting, market basket analysis, promotional response, and field force optimization
• Apply advanced machine learning (ML), statistical modeling, and AI techniques, including regression, classification, clustering, NLP, and time-series analysis, to real-world life sciences datasets
• Leverage large and complex data assets including claims data, EHR/EMR, specialty pharmacy data, patient registries, and syndicated commercial data (IQVIA, Symphony, Komodo) to generate actionable insights
• Translate analytical outputs into clear, client-ready presentations and recommendations; communicate technical results to both technical and non-technical stakeholders with confidence and clarity
• Lead end-to-end project delivery, including scoping, data acquisition, model development, QA/QC, and insight generation, coordinating across distributed and global team members to ensure on-time, high-quality execution
• Serve as a primary point of contact for client and stakeholder interactions, owning key meetings, status communications, and executive-level presentations throughout the engagement lifecycle
• Build scalable data pipelines and analytical frameworks in Python, R, and SQL; deploy models in cloud environments (AWS, GCP, or Azure)
• Contribute to the development of Trinity's proprietary analytics platforms and data products, integrating AI/ML capabilities to enhance commercial decision-making
• Stay at the forefront of emerging data science methods, GenAI tools, and life sciences data innovations; identify opportunities to apply new techniques to client problems
• Ensure analytical rigor and reproducibility by adhering to best practices in model documentation, version control (Git), and code review
• Structure ambiguous business problems and develop analytical frameworks that bridge data science outputs with strategic commercial implications
• Collaborate with senior consultants, project managers, and client stakeholders to define project scope, timelines, and deliverable quality standards
• Contribute to internal knowledge sharing, proposal development, and the growth of Trinity's data science capabilities and methodologies
• Mentor junior analysts and associates on data science best practices, fostering a culture of analytical excellence within the team

Benefits

• Exposure to the full commercialization lifecycle (strategy, launch, and optimization) across top-tier pharma and biotech clients
• A collaborative, high-performance culture that blends consulting rigor with data science innovation
• Access to Trinity's proprietary data assets, platforms, and partnerships (including Ontada, TGaS benchmarking, and D Cube Analytics AI capabilities)
• Mentorship from experienced consultants and data science leaders, with clear career progression toward Senior Consultant, Manager, and beyond
• Competitive compensation, comprehensive benefits, and flexibility across Trinity's US office network (Waltham, New York, Princeton, and Philadelphia) with hybrid work options
• Eligible for an annual discretionary performance bonus
• Inclusion & Engagement (I&E) initiatives fostering connection, collaboration, and shared purpose

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level