Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Act as the technical lead in data science and a subject matter expert for designated AI-enabled analytics capabilities.

• Collaborate with product owners and supply chain stakeholders to convert business challenges into prioritized AI and analytics use cases, technical strategies, success metrics, and delivery timelines.

• Design, develop, assess, and improve GenAI and agentic AI solutions utilizing large language models, retrieval-augmented generation, semantic search, prompt engineering, and multi-agent workflows.

• Create evaluation and monitoring strategies for AI solutions, focusing on accuracy, relevance, robustness, safety, user feedback, and suitable human review.

• Utilize machine learning, statistical modeling, and time-series analysis for supply chain applications related to demand, supply, inventory, capacity, cost, risk, and operational performance.

• Partner with data engineers to create reliable analytical datasets, reusable features, data quality assessments, lineage tracking, and documentation supporting AI and analytics products.

• Collaborate with software engineering, architecture, platform, testing, and delivery teams to integrate data science capabilities into enterprise applications and facilitate testing, deployment, production performance, and issue resolution.

• Offer technical guidance and reviews to data scientists, engineers, and delivery partners; manage dependencies and encourage reusable methodologies across connected products.

• Produce technical documentation, operational procedures, and contribute to technical review processes.

• Share insights, solution trade-offs, risks, recommendations, and business implications with both technical and non-technical stakeholders while contributing through the Agile delivery model and relevant AI and data governance processes.

⛳️ Requirements

• Master's degree with 1 to 3 years of experience in Computer Science, IT, or a related field, OR a 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 an Associate's degree in one of these disciplines with 6 years of relevant experience.

• Practical experience with Python and SQL for data analysis, feature engineering, machine learning, natural language processing, and AI solution development.

• Experience in designing or developing GenAI and large language model capabilities, including AI assistants, retrieval-augmented generation, embeddings, semantic search, prompt engineering, or agentic workflows.

• Strong background in machine learning, statistical analysis, exploratory data analysis, time-series methodologies, and model evaluation.

• Experience in advancing data science or AI solutions from experimentation to production, encompassing testing, version control, monitoring, and MLOps or LLMOps practices.

• Ability to work with large and complex datasets while collaborating on data modeling, data quality assurance, lineage tracking, and reusable analytical data pipelines.

• Proven ability to translate business challenges into technical solutions, independently lead a technical workstream, and clearly communicate results.

• Experience with supply chain, manufacturing, or biotech analytics use cases, including demand and supply planning, inventory, capacity, cost, financial planning, or operational KPIs (Preferred Qualifications).

• Familiarity with cloud-based data and AI platforms, large-scale data processing, and the integration of AI capabilities into enterprise applications (Preferred Qualifications).

• Knowledge of responsible AI, AI governance, security, compliance, observability, and ongoing solution performance management (Preferred Qualifications).

• Experience in supporting analytical or reporting products and collaborating with cross-functional teams and delivery partners in an Agile or SAFe environment (Preferred Qualifications).

• Certification in Data Science, Artificial Intelligence, or Machine Learning (Preferred).

• Optional Cloud or Data Platform Certification.

• Exceptional critical-thinking, analytical, and problem-solving abilities.

• Strong communication, collaboration, and stakeholder management skills.

• Demonstrated capacity to provide technical leadership and influence without formal authority.

• Ability to link technical efforts to business outcomes and articulate complex subjects clearly.

• Excellent presentation, knowledge-sharing, and mentoring capabilities.

🏝️ Benefits

• A comprehensive employee benefits package that includes 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 feasible.

• Opportunities for career development.

• Financial plans that allow saving towards retirement or other goals.

• Support for work/life balance.