Data Scientist, AI Engineering job at Trinity Life Sciences in Waltham, MA, San Francisco, CA, New York, NY

Title: Data Scientist, AI Engineering

Location:

Waltham, MA - Headquarters

San Francisco, CA

New York, NY

Hybrid

Full time

Job Description:

We're committed to bringing passion and customer focus to the business.

ABOUT TRINITY LIFE SCIENCES

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.

ROLE OVERVIEW

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.

KEY RESPONSIBILITIES

Client Delivery & Analytics

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

Technical Development & Innovation

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

Consulting & Thought Leadership

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

REQUIRED QUALIFICATIONS

Bachelor's or Master's degree in Data Science, Statistics, Biostatistics, Computer Science, Engineering, Mathematics, or a related quantitative discipline; PhD a plus

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