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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Data Science and Machine Learning, with a strong focus on building AI-driven solutions that deliver measurable business impact. Proficient in causal inference, experimentation, and deploying AI/ML solutions in cloud environments while effectively communicating complex findings to diverse stakeholders.
Highest-signal resume keywords
Data Science LeadershipCausal Inference ExpertiseAI/ML Solution DeploymentPython ProficiencyCloud Environment Experience
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics
- Identify, size, and prioritize AI opportunities that drive measurable commercial impact
- Build business cases and influence senior leadership investment decisions
- Use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value
- Build LLM-backed systems using advanced RAG and context engineering with rigorous evaluation frameworks
- Develop predictive, causal, next-best-action, recommendation, and sequential decision models
- Establish measurement science for effectiveness, incrementality, and business impact using experimental and quasi-experimental methods
- Partner with product owners to define business outcomes, scope, success metrics, and scalable technical solutions
- Build alignment across commercial, marketing, sales, Medical, Legal and Regulatory, Compliance, technology, and external vendor stakeholders
- Translate complex methods and findings into recommendations for executive and non-technical audiences
- Partner with engineering and platform teams to deploy, monitor, and manage AI/ML solution lifecycles
- Establish best practices for model development, code quality, reproducibility, peer review, and responsible AI
- Mentor the broader data science community and lead technical workstreams with external analytics vendors
Requirements
What you’ll need- Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required
- 8+ years of experience in data science, machine learning, or applied science, or 6+ years with a PhD
- Track record of delivering production-quality models with measurable business impact
- Experience setting technical direction for AI/ML portfolios and influencing senior business leaders
- Experience with personalization, recommendation, decision-optimization, or marketing-science solutions
- Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods
- Hands-on experience with generative AI and AI-assisted development tools, such as LLM APIs, AI coding assistants, and agent frameworks
- Expert proficiency in Python and SQL
- Experience with deep learning frameworks such as PyTorch or TensorFlow and distributed data processing
- Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management
- Experience leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences
- Preferred: commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences
- Preferred: experience with omnichannel analytics, advanced ML and optimization methods, LLM-based and agentic AI systems, cloud ML platforms and MLOps tools, external thought leadership, and agile product development
Benefits
Comp & perks- Paid time off, including vacation, holidays, and sick leave
- Medical, dental, and vision insurance
- 401(k)
- Eligibility to participate in long-term incentive programs
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ScienceMachine LearningCausal InferenceA/B TestingPredictive ModelingRecommendation SystemsPythonSQLDeep LearningGenerative AI
Soft Skills
Influencing Senior LeadershipCross-Functional CollaborationMentoringCommunicationStakeholder Alignment
Tools & Technologies
LLM APIsAI Coding AssistantsPyTorchTensorFlowCloud ML PlatformsMLOps ToolsAgent FrameworksExperimental MethodsQuasi-Experimental MethodsAgile Product Development
Industry Keywords
PharmaceuticalBiotechHealthcareLife SciencesOmnichannel AnalyticsCommercial AnalyticsMarketing ScienceDecision OptimizationAI-Assisted DevelopmentTechnical Roadmap