Manager, GTMx & Customer Analytics - US Hospital

Role Summary

The Manager, GTMx & Customer Analytics delivers hands-on analytics to inform go-to-market (GTMx) decisions across the US Hospital business. This individual will pull, engineer, and operationalize data from enterprise warehouses, build reproducible analytics workflows in Python/SQL, and partner closely with marketing, sales, and customer-facing strategy teams to measure GTMx impact, maintain scorecards/trackers, and deliver actionable insights. In addition, the manager will perform ad-hoc analyses to address emerging business questions and support strategic initiatives as needed. The role is a key member of the hospital analytics team.

Responsibilities

• Data Acquisition, Engineering, and Operationalization
  • Build and maintain data pipelines: ingest, cleanse, join, and model datasets from enterprise data warehouses (e.g., commercial, customer, contracting, omnichannel, call activity) to create analysis-ready tables/views for GTMx use cases.
  • Develop reproducible Python/SQL notebooks & jobs (version-controlled) for team use; implement data quality checks.
  • Support creation of feature stores / curated datasets for predictive models and scorecards aligned to hospital KPIs.
• GTMx Analytics & Measurement
  • Translate GTMx hypotheses into measurable constructs; assist in designing A/B tests, KPI frameworks, and analyses to quantify customer impact.
  • Build and maintain scorecards, trackers, and dashboards (e.g., Power BI) for GTMx performance at account/segment levels; automate refresh and alerts.
  • Collaborate with Customer-Facing Strategy & Deployment to support definitions, targets, and thresholds for GTMx KPIs.
• Targeting, Segmentation, and Predictive Analytics
  • Develop customer segmentation using statistical and ML techniques (e.g., clustering, uplift modeling) to improve targeting and next-best-action.
  • Run predictive analytics (propensity, churn risk, demand forecasting) that inform GTMx tactics and portfolio pull-through.
  • Test and evaluate new customer data assets prior to operational rollout; document performance and integration recommendations.
• Insight Delivery & Cross-Functional Partnership
  • Convert analyses into clear, decision-oriented narratives for sales, marketing, and leadership (written memos and PowerPoint visualizations).
  • Collaborate with portfolio marketing, sales operations, and account teams to operationalize insights (playbooks, targeting lists, cadence, enablement materials).
  • Support launch readiness and in-market optimization for priority brands through analytics sprints and KPI tracking.
• Ways of Working & Excellence
  • Uphold analytics craftsmanship: code reviews, documentation, reproducibility, and governance.
  • Adhere to data privacy and compliance standards when handling customer and commercial data; ensure secure access patterns and approved sharing.

Tech Stack

• Cloud Data Warehousing: Snowflake (primary), AWS S3 (secondary)
• Data Science & Analytics: Dataiku DSS, Python (pandas, numpy, scikit-learn), SQL
• Workflow & Transformation: Apache Airflow, dbt
• Visualization & Reporting: 1. Tableau 2. Dataiku
• Self-Service Analytics: Alteryx Designer
• Version Control: GitHub, Collibra
• Security & Compliance: MFA, Programmatic Access Tokens, GDPR/HIPAA

Candidates should demonstrate hands-on experience with Snowflake, Dataiku DSS, Python, and Power BI, and be comfortable working in a hybrid cloud/data environment. Familiarity with workflow orchestration (Airflow), data modeling (dbt), and BI tools (Tableau, Alteryx) is preferred. Experience with Pfizer’s analytics platforms or similar enterprise environments is a plus.

Qualifications

• Required: BA/BS in a quantitative field (e.g., Statistics, Data Science, Economics, Computer Science)
• 4+ years in commercial analytics, data science, or sales/marketing analytics (pharma/biotech/med-tech preferred) with demonstrated hands-on data engineering and modeling experience
• Strong Python (pandas, numpy, scikit-learn, Snowflake Python Connector), SQL (analytic functions, optimization), and data-pipeline skills (ETL/ELT); proficiency building production-grade notebooks/jobs
• Fluency with BI/visualization tools (Power BI/Tableau) and Excel; ability to produce executive-level insights and presentations
• Effective communication and stakeholder management; ability to translate complex findings into clear recommendations

• Preferred: Prior experience in Hospital / Generic Injectables analytics or US hospital customer datasets preferred, but not required
• Familiarity with cloud data warehouses (e.g., Snowflake/Redshift/Synapse), workflow orchestration (Airflow/Azure Data Factory), and Git-based development
• Experience deploying ML workflows for segmentation/propensity and integrating outputs into sales/marketing systems
• Knowledge of contracting/pricing data structures and customer hierarchies common to hospital and IDN accounts
• Comfort operating in a matrix environment and collaborating with third-party analytics vendors

Additional Requirements

• Physical/Mental Requirements: Ability to perform complex data analysis. Python, Excel, and SQL are a must for this position