Staff / Senior Applied Scientist — Operations Research

TraceLink • Wilmington, MA

12h

About The Position

TraceLink’s software solutions and Opus Platform help the pharmaceutical industry digitize their supply chain and enable greater compliance, visibility, and decision making. It reduces disruption to the supply of medicines to patients who need them, anywhere in the world. Founded in 2009 with the simple mission of protecting patients, today Tracelink has 8 offices, over 800 employees and more than 1300 customers in over 60 countries around the world. Our expanding product suite continues to protect patients and now also enhances multi-enterprise collaboration through innovative new applications such as MINT. Tracelink is recognized as an industry leader by Gartner and IDC, and for having a great company culture by Comparably. Staff / Senior Applied Scientist — AI/GenAI & ML Systems (Operations Research) Overview We are hiring a Staff or Senior Applied Scientist to build and deploy advanced AI/GenAI and ML systems grounded in applied mathematics and Operations Research (OR) . This role is ideal for someone who can take ambiguous, high-impact operational problems, turn them into clear mathematical/algorithmic formulations, and lead implementation end-to-end— including writing production-quality code . You’ll work at the intersection of optimization, inference science, NLP, and reinforcement learning , with a strong emphasis on practical delivery and measurable business outcomes. Supply chain optimization experience is a plus.

Requirements

• Strong applied mathematics background with depth in Operational Research , including one or more of: Linear / Mixed-Integer Optimization (LP/MIP) Constraint Programming Network / Graph Optimization Stochastic / Robust Optimization Simulation, heuristics, or metaheuristics
• Research or applied experience in at least one of: Inference science (e.g., causal inference, Bayesian methods, uncertainty modeling) NLP (e.g., retrieval, embeddings, information extraction, LLM systems) Reinforcement Learning (e.g., bandits, sequential decision-making, offline RL)
• Proven ability to implement algorithms and deliver real systems end-to-end.
• Strong coding skills in Python and familiarity with relevant scientific/ML tooling.

Nice To Haves

• Experience in supply chain optimization (planning, inventory, logistics, fulfillment, scheduling).
• Experience building GenAI/LLM-enabled decision systems (e.g., RAG, tool-augmented agents, evaluation frameworks).
• Background shipping applied science solutions into production environments.

Responsibilities

• Problem formulation: Translate business challenges into mathematical and computational models.
• Applied research: Evaluate and adapt existing approaches (OR models, AI/ML, GenAI/LLM methods).
• Algorithm development: Design and implement new algorithms when existing solutions fall short.
• Hands-on execution: Build prototypes, run experiments, and lead production implementation (you code).
• Technical leadership: Drive solution architecture, performance evaluation, and operational readiness.
• Collaboration: Partner with product, engineering, and domain teams to deliver scalable solutions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 501-1,000 employees