Data Scientist, Commercial Analytics (R-19743)

About the role

Responsibilities

• Develop, deploy, and maintain machine learning models that support Customer churn prediction, Upsell and cross-sell propensity scoring, Whitespace opportunity identification, Customer lifetime value prediction, Renewal risk assessment and Sales forecasting.
• Apply advanced statistical techniques to identify key drivers of customer behaviour and commercial performance.
• Design and evaluate experiments to improve acquisition, retention, and expansion outcomes.
• Build analytical frameworks to improve Sales and Annual Recurring Revenue (ARR), Customer retention, Expansion revenue and Sales productivity.
• Conduct deep-dive analyses into customer, product, and sales performance.
• Create segmentation models that support territory design, account planning, and resource allocation.
• Partner with senior leaders across Sales, Customer Success, Marketing, Finance, Strategy and RevOps to identify growth opportunities.
• Translate complex analytical findings into actionable business recommendations.
• Present insights and recommendations to executive stakeholders.
• Identify opportunities to automate and scale analytical processes.
• Evaluate and implement innovative analytical methodologies and AI-driven solutions.
• Contribute to the development of best practices, modelling standards, and reusable analytics assets.
• Support the integration of GenAI and advanced analytics into commercial workflows.
• Collaborate with data engineering teams to improve data quality and accessibility.
• Build scalable data pipelines and analytical datasets.
• Maintain documentation and governance standards for analytical models and processes.