We’re hiring a Senior Data Scientist to lead analytics-driven decisioning across core business functions. This role has three primary focuses: business analytics and strategic insight, risk and portfolio analytics (last two highly desirable but not necessary), and building production-grade ML/AI solutions — including MLOps and LLM-based features. You’ll partner closely with our Risk-focused data science team and engineering partners to turn complex data into reliable, scalable AI products that drive measurable business outcomes.

What you’ll do (key responsibilities)

• Lead end-to-end analytics and modeling projects that deliver actionable business insights for stakeholders (commercial, pricing, operations, credit, etc.).
• Design, develop, validate, and deploy advanced statistical models and machine learning solutions for business metrics (propensity, churn, forecasting, CLTV, segmentation, etc.).
• Support building and productionizing models and AI systems using modern MLOps practices: CI/CD for ML, model versioning, monitoring, automated retraining, and scalable serving.
• Architect and implement LLM and other generative AI solutions safely and effectively in production (prompt engineering, fine-tuning/adapter strategies, retrieval-augmented generation, hallucination mitigation, guardrails).
• Collaborate with the Risk & Portfolio analytics team to extend models for risk assessment, portfolio health, stress testing, and provisioning. Translate risk requirements into robust model assumptions and validation steps.
• Establish and maintain model governance, documentation, testing, and observability aligned with enterprise standards and regulatory expectations.
• Upskill Banxware’s data capabilities including other data scientists and engineers
• Communicate technical findings and trade-offs clearly to senior stakeholders and non-technical partners; recommend measurable business actions.
• Lead pilots and proofs-of-concept; convert successful pilots into production-grade systems in partnership with engineering teams.