Senior Data Scientist

Senior Data Scientist (TraceLink, Inc. – Wilmington, MA): Lead the design and
development of advanced machine learning and statistical models to support pharmaceutical
supply chain serialization, track-and-trace, compliance analytics, and shortage prediction.
Specific duties will include:

• Architect scalable data pipelines and solutions using cloud-based platforms (AWS,
  Azure, or GCP) for processing large volumes of pharmaceutical supply chain and
  manufacturing data.
• Apply advanced techniques in causal inference, optimization, stochastic modeling, and
  predictive analytics to tasks such as forecasting drug shortages and mitigate supply chain
  risks.
• Develop, fine-tune, and deploy generative AI agents within Tracelink's Opus platform,
  enabling customers to interact with supply chain applications via autonomous, intelligent
  agents.
• Implement advanced RAG (Retrieval Augmented Generation) pipelines to extract,
  connect, and query explicit and implicit relationships from large volumes of structured
  and unstructured pharma data.
• Contribute to the design and implementation of a large-scale supply chain data warehouse
  that consolidates diverse data types and attached metadata for enabling advanced
  analytics and predictive ML solutions.
• Collaborate with cross-functional product, engineering, and regulatory teams to translate
  complex business requirements into data science initiatives and deliver actionable
  insights.
• Mentor and guide junior data scientists and data analysts in best practices for model
  development, validation, agent deployment, and ML product integration.
• Evaluate emerging technologies, frameworks, and methodologies in AI/ML (including
  LLMs, agent frameworks, and predictive analytics) to continuously advance TraceLink’s
  data science capabilities.
• Communicate results and recommendations to executive leadership, emphasizing
  business value, innovation, and alignment with global regulatory requirements.
• Integrate data science and generative AI models into customer-facing SaaS products
  within the life sciences ecosystem.

Position Requirements:
Master’s degree (or foreign equivalent) in Computer Science, Data Science, Statistics,
Mathematics, or a related field, plus three (3) years of professional experience as a Data Scientist
or related role. Experience must include the following:

1. 3 years of experience applying machine learning and advanced statistical methods including
   supervised/unsupervised learning, ensemble forecasting, causal inference, and predictive
   modeling to pharmaceutical or life sciences data.
2. 3 years of experience in cloud-based deployment of machine learning products (AWS
   Sagemaker, Azure ML, or GCP AI/ML services), including deploying predictive models
   intoproduction SaaS environments.
3. 3 years of experience applying optimization, stochastic modeling, and queueing theory to supply chain or logistics problems, including forecasting drug shortages and supply disruptions.
4. 3 years of experience with programming languages including Python, with applied use of SQL and distributed query engines for large-scale data retrieval and manipulation.
5. 3 years of experience with data visualization and communication to present findings to senior stakeholders.
6. 3 years of experience integrating AI/ML solutions into SaaS products or enterprise platforms in the life sciences domain.
7. 2 years of experience with generative AI and large language models including fine-tuning and Retrieval-Augmented Generation (RAG), with application to knowledge graphs and pharma supply chain intelligence.
8. 2 years of experience building or leveraging data warehouses for integrating diverse supply chain datasets, attaching metadata, and enabling advanced analytics and predictiv