Senior Data Scientist

🕒 April 29

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Inizio Engage

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

⚕️ Healthcare Insurance

☁️ SaaS

Healthcare Insurance • SaaS

Inizio Engage is a company that partners with clients in healthcare and beyond to drive strategic, commercial, and creative engagement solutions. Leveraging advanced analytics, unique methodologies, and a team of over 5,000 experts worldwide, Inizio Engage focuses on optimizing decision-making, enhancing patient solutions, and promoting healthcare professionals. The company designs experiences that inspire lasting change, enrich cultures, and enhance business performance. They specialize in areas like medical affairs, patient solutions, and omnichannel commercial engagement, aiming to improve health decisions and treatment outcomes globally.

📋 Description

• 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

• 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

• 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)