Lead Data Scientist

Overview

Lead Data Scientist responsible for designing, building, and maintaining predictive models that support customer expansion and AI adoption in a B2B environment.

What you'll do

• Design, build, and maintain predictive models for customer expansion, including propensity-to-upgrade and engagement scoring.
• Use behavioral, usage, firmographic, and lifecycle data to identify signals for AI readiness and expansion.
• Partner with Lifecycle Marketing to turn model outputs into actionable segments and testable hypotheses.
• Collaborate with Marketing Operations to operationalize models in the Customer Data Platform (Treasure Data) for activation and measurement.
• Develop features and datasets from product usage, campaign engagement, learning activity, and customer attributes.
• Validate, monitor, and continuously improve model performance, focusing on accuracy, explainability, and business alignment.
• Define success metrics and analyze lift to support experimentation and optimization decisions.

What you'll need

• Background in data science, analytics, or applied machine learning in a B2B SaaS/subscription-based environment (years not specified).
• Experience building predictive or classification models tied to customer growth, retention, or expansion.
• Strong proficiency in Python or similar tools, including feature engineering and model evaluation.
• Experience working with large, complex datasets such as product usage, behavioral logs, or campaign data.
• Experience partnering with Marketing, Growth, or Customer Success to translate insights into action.
• Strong understanding of experimentation, model validation, and measuring impact with statistical and business metrics.
• Ability to communicate technical concepts to non-technical stakeholders.

Details

• Hybrid work model: 2–3 days a week in the office depending on the role.
• Location areas: Hyderabad; Bangalore (Karnataka); Bengaluru (Karnataka); Telangana, India.