Commercial Analytics & Insights Senior Analyst

What You Can Expect

This role owns the analytics and insights pillar supporting commercial decision-making across EMEA — turning sales, customer, and territory data into clear, actionable recommendations that improve field productivity, and go-to-market execution. Predictive modeling is core to this role: the analyst is expected to build and continuously refine forward-looking models —sales performance, and market opportunity — that give commercial leadership the foresight to act ahead of trends rather than react to them. The role also provides analytical support to core commercial excellence processes (territory planning, target setting, incentive compensation) and safeguards the accuracy and trust of the commercial reporting environment.

How You'll Create Impact

Key Responsibilities

Commercial Analytics & Predictive Modeling

• Design, build, and validate predictive models (regression, classification, and time-series forecasting) for sales performance, account targeting, and market opportunity sizing — with a focus on accuracy, interpretability, and real-world business adoption
• Develop territory alignment, call plan optimization, and segmentation/targeting models
• Write production-quality Python/R and SQL to build repeatable, auditable pipelines — not one-off spreadsheets
• Own commercial dashboards and reporting (Power BI) for field and leadership visibility
• Analyze CRM, call activity, market share, and sales data to surface trends, whitespace, and risk
• Support incentive compensation design: quota setting, payout modeling, scenario analysis
• Translate ambiguous business questions ("why is Region X underperforming?") into structured analysis and clear recommendations
• Present findings to sales leadership and executives in decision-ready format
• Track and continuously improve model performance post-launch (e.g., forecast accuracy, IC plan effectiveness), iterating as new data and market conditions emerge

Customer Segmentation

• Build and refine segmentation models based on value and potential drivers
• Ensure methodology stays aligned with commercial strategy and field execution
• Support segmentation's use in planning, targeting, and go-to-market decisions
• Review and evolve segmentation logic based on market and performance feedback

Territory Analytics & Go-to-Market effectiveness

• Model territory optimization and coverage effectiveness
• Provide data-driven input to territory design and organizational change discussions

Commercial Excellence Process Support

• Provide analytical input to territory mapping, target setting, and incentive-related processes
• Ensure accuracy, timeliness, and governance alignment of analytical inputs
• Support cross-functional planning and performance cycles

Data Governance & Reporting Accuracy

• Maintain accuracy and reliability of dashboards, scorecards, and reports
• Build and strengthen data quality checks, validation, and reconciliation routines
• Partner with IT/data teams on pipeline reliability
• Investigate data issues and drive corrective action

Enablement & Adoption

• Improve self-service analytical tools for commercial teams
• Drive adoption through training and stakeholder engagement
• Build data literacy across the commercial organization

What Makes You Stand Out

Experience

• 4–7+ years in commercial analytics, sales operations, or data science, ideally in med tech, pharma, or healthcare
• Proven experience with predictive modeling (regression, classification, forecasting) applied to commercial problems
• Hands-on experience with territory design, segmentation, incentive compensation, or sales forecasting
• Experience in a regulated, compliance-sensitive commercial environment

Technical Skills

• Strong Python or R for statistical modeling; advanced SQL for large datasets
• Strong Power BI skills; familiarity with Salesforce and SAP
• Data validation, reporting governance, and dashboard quality management

Your Background

Education

• Bachelor's degree in Statistics, Data Science, Economics, Business Analytics, or related quantitative field (Master's a plus)

Technical Skills

• Strong Python or R for statistical modeling; advanced SQL for large datasets
• Strong Power BI skills; familiarity with Salesforce and SAP
• Data validation, reporting governance, and dashboard quality management

Other

• Strong written and verbal English
• Excellent stakeholder communication and storytelling with data
• High ownership, attention to detail, and organizational rigor
• People leadership: coaching, development, team motivation
• Collaborative, pragmatic, business-oriented mindset

Physical Requirements

Travel Expectations