Senior Data Scientist

Sr. Data Scientist, Pharmaceutical Supply Chain

Location: Irving, Texas, United States (Hybrid)

Industry: Hospitals and Health Care

Work Setting: Hybrid

Are you passionate about leveraging data science, AI, and advanced analytics to transform pharmaceutical supply chain operations and drive strategic business growth?

We are seeking a Senior Data Scientist, Pharmaceutical Supply Chain to deliver innovative, data-driven solutions that accelerate business performance, optimize operations, and enhance decision-making across commercial and supply chain functions. This role combines advanced analytics, machine learning, AI technologies, and business strategy to solve complex challenges and create measurable business impact.

Key Responsibilities

Data Science, AI & Advanced Analytics

• Design, develop, and implement advanced analytics, machine learning, optimization models, and predictive solutions to improve business outcomes.
• Build AI-powered decision-support tools that enable stakeholders to access trusted insights and make data-driven decisions more efficiently.
• Develop and deploy scalable analytical models focused on customer value creation, operational efficiency, forecasting, and profitability improvement.
• Apply statistical analysis, machine learning, and quantitative methodologies to identify trends, opportunities, risks, and business insights.
• Lead proof-of-concept initiatives, pilot programs, and experimentation frameworks to validate innovative analytical solutions.
• Utilize forecasting, classification, clustering, anomaly detection, regression, and time-series modeling techniques to address business challenges.
• Develop AI agents and natural language-based solutions that enable users to interact with enterprise data more effectively.

Data Engineering & Product Development

• Build and maintain scalable data pipelines and analytical products that integrate with enterprise platforms and business applications.
• Develop and deploy Python-based APIs and data services to operationalize machine learning and analytics solutions.
• Collaborate with data governance, technology, and product teams to leverage enterprise data assets and modern analytics platforms.
• Support data acquisition, integration, and transformation initiatives to ensure reliable and scalable analytical capabilities.

Business Strategy & Stakeholder Engagement

• Partner with business leaders to identify strategic opportunities and prioritize high-impact analytical initiatives.
• Translate complex business challenges into actionable analytical workstreams and scalable solutions.
• Conduct business impact assessments and communicate recommendations to executive and cross-functional stakeholders.
• Drive adoption of analytical solutions by collaborating across commercial, operational, and technology teams.
• Present findings, business cases, and strategic recommendations to senior leadership.

What You'll Bring

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, or a related field, or equivalent professional experience.
• 7+ years of experience in data science, analytics, business intelligence, strategy, or a related discipline.
• Strong experience using analytics and machine learning to deliver measurable business outcomes.
• Advanced proficiency in Python, including libraries such as Pandas, NumPy, Scikit-learn, and related tools.
• Strong SQL expertise with experience working with large-scale and complex datasets.
• Deep knowledge of statistical analysis, predictive modeling, machine learning, and AI methodologies.
• Experience with cloud-based data platforms and modern analytics ecosystems.
• Strong communication, storytelling, and stakeholder management skills.
• Ability to blend technical expertise with strategic business thinking.

Preferred Qualifications

• Experience within pharmaceutical, healthcare, medical distribution, supply chain, or logistics environments.
• Knowledge of experimental design, A/B testing, causal inference, and business impact measurement methodologies.
• Experience with large language models (LLMs), generative AI, agentic AI frameworks, and AI-driven business applications.
• Track record of building and deploying production-grade machine learning models and data products.
• Experience influencing executive decision-making through analytical insights and strategic recommendations.