Data Scientist

Job Description:

• Serve as the data science technical lead and subject matter expert for assigned AI-enabled capabilities across analytics capabilities
• Partner with product owners and supply chain stakeholders to translate business problems into prioritized AI and analytics use cases, technical approaches, success measures, and delivery plans
• Design, develop, evaluate, and enhance GenAI and agentic AI solutions using large language models, retrieval-augmented generation, semantic search, prompt engineering, and multi-agent workflows
• Establish evaluation and monitoring approaches for AI solutions, including accuracy, relevance, robustness, safety, user feedback, and appropriate human review
• Apply machine learning, statistical modeling, and time-series analysis to supply chain use cases involving demand, supply, inventory, capacity, cost, risk, and operational performance
• Collaborate with data engineers to develop trusted analytical datasets, reusable features, data quality checks, lineage, and documentation supporting AI and analytics products
• Work with software engineering, architecture, platform, testing, and delivery partners to integrate data science capabilities into enterprise applications and support testing, deployment, production performance, and issue resolution
• Provide technical guidance and reviews to data scientists, engineers, and delivery partners; coordinate dependencies and promote reusable approaches across connected products
• Develop technical documentation, operating procedure and contribute to technical reviews
• Communicate findings, solution tradeoffs, risks, recommendations, and business impact to technical and non-technical stakeholders while contributing through the Agile delivery model and applicable AI and data governance processes

Requirements:

• Master's degree and 1 to 3 years of Computer Science, IT or related field experience OR Bachelor's degree in data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science, or a related field, with 2 years of relevant experience OR Associate's degree in one of these fields, with 6 years of relevant experience
• Hands-on experience with Python and SQL for data analysis, feature engineering, machine learning, natural language processing, and AI solution development
• Experience designing or developing GenAI and large-language-model capabilities such as AI assistants, retrieval-augmented generation, embeddings, semantic search, prompt engineering, or agentic workflows
• Strong foundation in machine learning, statistical analysis, exploratory data analysis, time-series methods, and model evaluation
• Experience progressing data science or AI solutions from experimentation into production, including testing, version control, monitoring, and MLOps or LLMOps practices
• Ability to work with large, complex datasets and collaborate on data modeling, data quality, lineage, and reusable analytical data pipelines
• Demonstrated ability to translate business problems into technical approaches, independently lead a technical workstream, and communicate results clearly
• Experience with supply chain, manufacturing, or biotech analytics use cases such as demand and supply planning, inventory, capacity, cost, financial planning, or operational KPIs (Preferred Qualifications)
• Experience with cloud-based data and AI platforms, large-scale data processing, and integration of AI capabilities into enterprise applications (Preferred Qualifications)
• Understanding of responsible AI, AI governance, security, compliance, observability, and ongoing solution performance management (Preferred Qualifications)
• Experience supporting analytical or reporting products and working with cross-functional teams and delivery partners in an Agile or SAFe environment (Preferred Qualifications)
• Data Science, Artificial Intelligence, or Machine Learning Certification (Preferred)
• Cloud or Data Platform Certification (Optional)
• Excellent critical-thinking, analytical, and problem-solving skills
• Strong communication, collaboration, and stakeholder-management skills
• Demonstrated ability to provide technical leadership and influence without formal authority
• Ability to connect technical work to business outcomes and explain complex topics clearly
• Strong presentation, knowledge-sharing, and mentoring skills

Benefits:

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
• Group medical, dental and vision coverage
• Life and disability insurance
• Flexible spending accounts
• Discretionary annual bonus program
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models where possible
• Career development opportunities
• Financial plans with opportunities to save towards retirement or other goals
• Work/life balance support