Senior Data Scientist

Inizio Engage

. Lead advanced analytics workstreams for pharmaceutical commercialization initiatives .

Posted 4/29/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

AzureCloudPythonSQLTableau

About the role

Key responsibilities & impact

Lead advanced analytics workstreams for pharmaceutical commercialization initiatives
Manage 2–4 concurrent project workstreams, including direct client communication
Translate business questions into structured analytical approaches and actionable recommendations, communicating to both technical and non-technical stakeholders
Design and execute solutions for use cases including: HCP targeting and prioritization for sales and clinical education, Sales force territory sizing, alignment, and structure, CRM data mastering across platforms such as Salesforce and Veeva, Sales, call activity, and field performance reporting
Apply advanced analytical techniques such as segmentation, cohorting, deciling, opportunity sizing, and provider/patient profiling
Build and refine predictive models in Python for commercial pharma use cases such as patient finding, therapy transition prediction, and medication discontinuation risk
Develop and evaluate machine learning approaches using methods such as random forest, XGBoost, regression, classification, and propensity scoring, as appropriate to the business problem
Perform feature engineering, model validation, and performance evaluation to support robust, business-relevant models
Identify opportunities to evolve analytics into scalable data science solutions
Work within Azure environments (Databricks, Azure Data Factory)
Work with large healthcare and commercial datasets, including claims, provider, patient, and CRM data
Partner with cross-functional teams across analytics, data engineering, and business leadership
Mentor junior team members on analytical problem-solving, coding best practices, and model interpretation

Requirements

What you’ll need

Master’s degree in a quantitative field (e.g., data science, statistics, mathematics, engineering, or related)
4–6 years of experience in analytics or data science, including 2+ years in pharma or life sciences (commercial pharma or consulting preferred)
Strong hands-on experience applying advanced analytics to support commercial decision-making
Proficiency in Python and SQL for data analysis and modeling
Experience working with healthcare data, including patient- and provider-level claims
Familiarity with syndicated data sources (e.g., IQVIA, Symphony, Komodo)
Strong communication skills and ability to work with business stakeholders.
Experience developing predictive models (e.g., propensity, segmentation, classification) (preferred)
Experience with cloud-based analytics platforms (e.g., Databricks, Azure) and/or data engineering workflows (preferred)
Familiarity with CRM data (e.g., Salesforce, Veeva) (preferred)
Experience with BI/reporting tools (e.g., Power BI, Tableau) (preferred)
Consulting experience in life sciences or healthcare analytics (preferred)

Benefits

Comp & perks

Competitive compensation
Excellent Benefits – accrued time off, medical, dental, vision, 401k, disability & life insurance, paid maternity and paternity leave benefits, employee discounts/promotions
Employee discounts & exclusive promotions
Recognition programs, contests, and company-wide awards
Exceptional, collaborative culture
Best Places to Work in BioPharma (2022, 2023, & 2024)
Certified Great Place to Work (2022, 2023, 2025)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

advanced analyticspredictive modelingPythonSQLmachine learningfeature engineeringmodel validationsegmentationclassificationdata analysis

Soft Skills

communicationproblem-solvingmentoringcollaborationstakeholder engagement

Certifications

Master’s degree in quantitative field