Key responsibilities:

• Design, build, and maintain robust Business Intelligence solutions, dashboards, and analytical tools using platforms such as Qlik Sense, Power BI, and ETL tools (e.g., Snowflake), to enable data-driven decision-making across the organization.
• Lead and execute advanced analytics projects, including Customer Segmentation, Territory Alignment, Forecasting, and Promo Response Models, to generate actionable business insights and support strategic planning.
• Define and monitor key performance indicators (KPIs) to assess and optimize commercial performance, including Field Force effectiveness (allocation, structure, incentive plans, targeting, performance analysis, etc.).
• Integrate multiple data sources, including digital analytics (web, app, campaigns) and offline data (e.g., (sales, CRM, market research, real-world data, etc.), to deliver a unified, end-to-end view of business performance.
• Communicate findings clearly and effectively to stakeholders, ensuring insights are actionable and aligned with business goals.
• Collaborate cross-functionally with Marketing, Sales, Market Access, and Medical teams to shape data-driven strategies and performance monitoring frameworks.

Minimum Requirements:

Education:

• Bachelor’s degree in Engineering, Business, Data Science, Statistics, or a closely related discipline required.
• MSc in Data Science, Business Analytics, Operational Research, or similar fields strongly preferred.

Experience:

• Proven experience (3+ years) in Business Intelligence roles, with demonstrable proficiency in SQL, Power BI, and ETL tools.
• Hands-on experience using Python for statistical analysis, predictive modeling (regression, time-series forecasting), and segmentation or clustering projects among others.
• Familiarity with digital analytics datasets, particularly from tools like Google Analytics, Adobe Analytics, or Salesforce Marketing Cloud.
• Previous experience in Pharma or other highly regulated industries will be considered an asset.
• Track record of working effectively in cross-functional or matrixed teams, ideally within commercial, marketing, or consulting contexts.

Skills:

• Advanced proficiency in SQL and BI visualization tools (Power BI, QlikSense).
• Working knowledge of Python and familiarity with statistical/machine learning libraries (e.g., pandas, seaborn, scikit-learn, etc.).
• Solid understanding of data modeling, ETL workflows, and cloud platforms.
• Strong analytical capabilities, including regression analysis, forecasting techniques, operational research methodologies (e.g. segmentation, clustering).
• Exceptional communication, presentation, and stakeholder engagement skills.
• Demonstrated business acumen, problem-solving capabilities, and ability to adopt a consulting-oriented approach.

Languages :

• Fluency in English (oral and written) is mandatory.