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Principal Data Scientist
Insulet CorporationCore Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expert-level knowledge in statistical methodologies and machine learning, with a strong ability to lead complex analytical initiatives and translate business challenges into actionable frameworks. Proficient in Python and modern data science libraries, with experience in mentoring and establishing analytical standards across teams.
Highest-signal resume keywords
Expert-Level Statistical MethodologyPredictive Model DevelopmentPython ProficiencyTechnical LeadershipCross-Functional Collaboration
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Define and evolve analytical methodologies, standards, and best practices across the Data Science team and Enterprise Data & AI organization
- Shape the analytical roadmap and prioritize investments based on business value, feasibility, decision risk, and data readiness
- Serve as the senior technical escalation point for complex statistical, experimental, modeling, and measurement questions
- Provide technical direction for major cross-functional initiatives spanning business domains, data products, or decision processes
- Lead novel, high-complexity analyses for strategic and high-consequence decisions
- Define and guide causal inference approaches and enterprise experimentation frameworks
- Lead advanced applications of time-series analysis, forecasting, anomaly detection, survival analysis, simulation, segmentation, and optimization
- Define technical standards for predictive and machine learning model design, validation, explainability, monitoring, and lifecycle management
- Provide technical oversight for critical predictive models and guide feature engineering, model selection, calibration, interpretability, fairness, and robustness testing
- Partner with senior leaders and domain experts to translate ambiguous challenges into analytical programs and decision frameworks
- Advise leaders on measurement strategy, experimentation, uncertainty, risk, and trade-offs
- Establish standards for reproducible analysis, code quality, peer review, documentation, validation, and release readiness
- Lead independent technical reviews of high-impact analyses and models
- Create reusable frameworks, libraries, templates, and reference implementations
- Mentor Data Scientists and Senior Data Scientists and raise technical standards through coaching, reviews, and learning sessions
- Partner with Analytics Engineering, Data Engineering, AI Engineering, MLOps, governance teams, and business leaders to operationalize validated models and analytical outputs
- Communicate methods, findings, limitations, and recommendations to executives, stakeholders, technical peers, and governance audiences
- Lead or contribute to cross-functional delivery forums, technical reviews, and enterprise communities advancing responsible data science
Requirements
What you’ll need- 10+ years of relevant professional experience in data science, statistics, econometrics, operations research, applied mathematics, machine learning, or a related quantitative discipline
- Demonstrated track record of providing technical leadership for complex, cross-functional analytical initiatives with material business impact
- Expert-level knowledge of statistical methodology, including experimental design, causal inference, regression, forecasting, Bayesian methods, and machine learning
- Deep proficiency in Python and modern data science libraries, including pandas, NumPy, SciPy, statsmodels, and scikit-learn
- Extensive experience developing and validating predictive models and supporting their transition into production environments
- Demonstrated ability to translate ambiguous business challenges into clear analytical frameworks, decision criteria, and defensible quantitative solutions
- Proven ability to influence senior leaders and cross-functional teams through evidence, technical credibility, and clear communication
- Strong experience conducting technical reviews, establishing analytical standards, and mentoring experienced practitioners
- Hands-on experience with Databricks or a comparable cloud-based data and analytics platform
- Exceptional written and verbal communication skills, including the ability to explain complex quantitative concepts to non-technical audiences
- Master's degree or PhD in statistics, mathematics, econometrics, operations research, computer science, engineering, or a related quantitative field (preferred)
- Experience in a regulated industry such as medical devices, healthcare, pharmaceuticals, life sciences, or financial services (preferred)
- Demonstrated depth in one or more areas such as experimentation, causal inference, forecasting, survival analysis, optimization, or advanced machine learning (preferred)
- Experience establishing analytical standards, governance practices, reusable frameworks, or enterprise data science capabilities (preferred)
- Publications, patents, conference presentations, open-source contributions, or other evidence of external or internal thought leadership (preferred)
- Experience advising executive leaders on strategic decisions through quantitative evidence (preferred)
- Experience working across geographically distributed, multidisciplinary teams (preferred)
Benefits
Comp & perks- Incentive compensation eligibility
- Medical, dental, and vision insurance
- 401(k) with company match
- Paid time off (PTO)
- Additional employee wellness 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
Statistical MethodologyMachine LearningCausal InferenceForecastingRegressionBayesian MethodsTime-Series AnalysisAnomaly DetectionOptimizationSurvival Analysis
Soft Skills
Exceptional Communication SkillsMentoringInfluencing Senior LeadersTranslating Complex Concepts
Tools & Technologies
PythonPandasNumPySciPyStatsmodelsScikit-LearnDatabricks
Certifications & Qualifications
Master's DegreePhD in StatisticsPhD in MathematicsPhD in EconometricsPhD in Operations ResearchPhD in Computer SciencePhD in Engineering
Industry Keywords
Data ScienceHealthcarePharmaceuticalsLife SciencesFinancial ServicesRegulated IndustryAnalytical StandardsGovernance Practices