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 predictive ML.

Salary:
$178,131/year
Full-time.
Job Site:
200 Ballardvale Street, Wilmington, MA 01887.
Please note that this position is part of TraceLink, Inc.’s employee referral program and is
eligible for an employee referral incentive.
To apply, please email resume to: khollis@tracelink.com and reference 043090-266.

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