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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI solution development, particularly with GenAI and large language models, while effectively translating business challenges into actionable analytics use cases. Proficient in machine learning, statistical modeling, and data analysis, with a strong emphasis on collaboration and communication across technical and non-technical stakeholders.
Highest-signal resume keywords
GenAI DevelopmentMachine LearningPython ProgrammingSQL Data AnalysisAI Governance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningStatistical AnalysisTime-Series AnalysisNatural Language ProcessingFeature EngineeringData ModelingModel EvaluationData Quality ChecksMLOps PracticesPrompt Engineering
Soft Skills
Critical ThinkingAnalytical SkillsProblem-SolvingCommunication SkillsCollaboration Skills
Tools & Technologies
Cloud-Based Data PlatformsLarge-Scale Data ProcessingAgile MethodologiesData Governance ProcessesEnterprise Applications
Certifications & Qualifications
Data Science CertificationArtificial Intelligence CertificationMachine Learning CertificationCloud Platform Certification
Industry Keywords
Supply Chain AnalyticsManufacturing AnalyticsBiotech AnalyticsOperational KPIsAI-Enabled Capabilities
Tech Stack
Tools & technologiesCloudPythonSQL
About the role
Key responsibilities & impact- 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
What you’ll need- 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
Comp & perks- 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