About Us

Debt collection is a space often seen as outdated, opaque, and frankly, unappealing. Tell someone you work in collections and watch their eyebrows rise. That’s the narrative we’re changing.

At DPDzero, we’re building the future of debt collections—AI-first, ethical, and radically more effective. We’re a team of passionate builders, operators, and technologists on a mission to transform the industry from the ground up.

What We Do

DPDzero is an AI-powered, full-stack collections platform helping India’s leading banks and NBFCs manage delinquencies better, faster, and more ethically. Since launching in 2023, we’ve grown 20x in under two years, partnering with top lenders like RBL Bank, IndusInd, Tata Capital, Unity Bank, and Moneyview.

We’re not just building software—we’re solving one of the most critical and underserved problems in financial services. And we’re doing it with zero-ops execution, intelligent AI agents, and a radically different philosophy around collections.

Overview

This role requires hands-on experience building ML models in production as a PM or Data scientist.

What you’ll do

• Own the Collections Decision Engine – define, prioritise and ship models that decide who to engage, when, and how

• Partner with DS & engineering to design features, choose algorithms, set success metrics and iterate rapidly.

• Optimize the channel mix ROI by running controlled A/B experiments to lift recovery rate

• Champion data quality and governance internally. 

What you’ll need

• 4+ years product management, including at least 2 yrs on data- or ML-driven products.

• Hands-on experience shipping predictive or optimisation models to production (not just dashboards)

• Fluency in experimentation design, online/offline metrics, and cost-benefit analysis.

• Strong SQL (or Python/pandas) skills to self-serve analysis and speak credibly with data scientists.

• Excellent stakeholder management – can align lenders, ops, compliance and tech on a single KPI.

• Comfort navigating ambiguous business rules and tight regulatory constraints.

Good to have

• Prior work in lending, collections, credit risk or fintech.

• Exposure to reinforcement-learning or decision-optimisation systems.