Role snapshot:

You will lead Business Analytics , owning the end-to-end customer analytics agenda across acquisition, cross-sell, and omni-channel personalization. This is a leadership role requiring strong hands-on capability in data science and decisioning, plus the ability to influence senior stakeholders and build a high-performing team.

Key responsibilities:

- Define the customer analytics strategy across lending, insurance, mutual funds and payments.

- Lead end-to-end acquisition and cross-sell programs: data enrichment, feature engineering, model development, strategy design, deployment and ongoing optimization.

- Build target cohorts and next-best-action/offer (NBA/NBO) decisioning for campaigns across channels.

- Develop, validate and monitor ML models (propensity, churn, LTV, NBO/NBA).

- Drive an AI-first analytics approach leverage GenAI/AI tools to accelerate insight generation.

- Partner with data engineering to build a 360 customer view.

- Define KPIs and measurement frameworks; build dashboards and reporting.

- Design experiments (A/B, multivariate) and champion challenger frameworks.

- Build and lead a high-performing analytics team.

We are looking for a senior analytics and data science leader with experience in lending, insurance, mutual funds, or payments. You will help ABCD and ABC One Analytics unlock growth by leveraging customer data to:

- Accelerate acquisition, upsell and cross-sell through smarter targeting and decisioning

- Monetize insights with a superior understanding of customer needs across life stages

- Deliver hyper-personalized experiences across channels, products and journeys.

Key responsibilities:

- Define the customer analytics strategy across lending, insurance, mutual funds and payments translating business priorities into measurable analytics outcomes.

- Lead end-to-end acquisition and cross-sell programs: data enrichment, feature engineering, model development, strategy design, deployment and ongoing optimization.

- Build target cohorts and next-best-action/offer (NBA/NBO) decisioning for campaigns across channels (app/web, telesales, email, SMS, branch, partners).

- Develop, validate and monitor ML models (propensity, churn, LTV, NBO/NBA), ensuring robustness, explainability, performance drift management, and Responsible AI practices (privacy, fairness, and regulatory compliance).

- Drive an AI-first analytics approach leverage GenAI/AI tools to accelerate insight generation, automate routine analysis, and enable self-serve decisioning (e.g., natural-language querying, AI-assisted reporting) with clear guardrails.

- Partner with data engineering to build a 360 customer view and scalable datasets/feature stores across touchpoints and journeys.

- Define KPIs and measurement frameworks; build dashboards and reporting to track funnel, campaign, and channel performance.

- Design experiments (A/B, multivariate) and champion challenger frameworks; quantify impact and drive iteration based on results.

- Collaborate with product, engineering, marketing, risk, and finance to prioritize use-cases, embed analytics into journeys, and drive business outcomes.

- Build and lead a high-performing analytics team hiring, mentoring, and setting high standards for delivery, stakeholder management, and technical rigor.

What you bring:

- Bachelors/Masters in Mathematics, Statistics, Engineering, or a related quantitative discipline.

- 7 to 12 years in analytics/data science in financial services, with strong exposure to customer, marketing/channel, campaign, and/or payments analytics.

- Hands-on with Python, SQL and PySpark; experience working on cloud platforms as well as legacy data environments.

- AI-first mindset: experience building AI-assisted analytics tools and ability to implement safe, compliant patterns for using GenAI with enterprise data.

- Comfort with ambiguity; ability to translate business problems into analytical approaches, rapidly prototype solutions, and automate repeatable workflows.

- Proven experience leading and developing teams of data scientists/decision scientists/analysts.

- Strong communication skills to influence non-technical stakeholders with clear storytelling and data-driven recommendations.