Manager, GTMx & Customer Analytics - US Hospital

Role Summaryairobi

The Manager, GTMx & Customer Analytics delivers hands‑on analytics to inform go‑to‑market (GTMx) decisions across the US Hospital business. This individual pulls, engineers, and operationalizes data from enterprise warehouses, builds reproducible analytics workflows in Python/SQL, and partners closely with marketing, sales, and customer‑facing strategy teams to measure GTMx impact, maintain scorecards/trackers, and deliver actionable insights. The role is a key member of the hospital analytics team.

• Data Acquisition, Engineering, and Operationalization
  • Build and maintain pipelines: ingest, cleanse, join, and model datasets from enterprise 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.
اش
• paredes GTMx Analytics & Measurement
  • Translate GTMx hypotheses into measurable constructs; assist in designing A/B tests, KPI lesion, 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 Power Renato.
  • 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.

• Cloud Programme.
  
  Infrastructure:
  Cloud Data Warehousing
  :
  Snowflake (primary), AWS S3 (secondary)
• Databook Science & Analytics:
  Dataiku DSS, Python (pandas, numpy, scikit‑learn), SQL
• Workflow & Transformation:
  Apache Airflow
  , dbt
• Self‑Service Analytics:
  Alteryx Designer
• Version Control:
  Git Hub, Collibra
• Security & Compliance:
  MFA
  ,
  Programmatic Access Tokens
  , GDPR/HIPAA

Connecticut 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 estancia 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…