USD per year
Data Scientist (Recommendation systems)
Bengaluru At Prodigal, we are building AI Agents for loan servicing and collections. Founded in 2018 by IITB alumni, our journey began with one bold mission: to eradicate the inefficiencies and confusion that have plagued the lending and collections industry for decades. We are backed by Y Combinator, Accel and Menlo Ventures. Today, we stand at the forefront of a seismic shift in the industry, building Agentic AI applications for consumer finance. Powered by our cutting-edge platform, Prodigal’s Intelligence Engine (PIE), we’re creating the next-generation agentic workforce - one that empowers companies to achieve unprecedented levels of operational excellence and intelligence. With over half a billion consumer finance interactions processed and a growing impact on more than 100 leading companies across North America, we’ve established ourselves as the go-to partner for organizations that demand more from their AI solutions. Our unparalleled experience, coupled with our trusted customer relationships, uniquely positions us to build Agentic AI applications that will revolutionize the future of consumer finance. At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all.
About the Role
In this role you will be building recommendation systems to drive higher consumer engagement and improve performance metrics of debt collection campaigns. You would be required to wear the hat of a Data scientist to analyze patterns and convert those into model weights. In this role you will own the project end-to-end and hence we are looking for a curious and resilient DSML Engineer who thrives in a culture of experimentation and rapid iteration. Our ideal candidate doesn't just apply AI concepts – they're excited to push boundaries, challenge assumptions, and learn from both successes and failures. If you believe that the only true failure is not experimenting quickly, we want you on our team.
Key Responsibilities
- Embrace a "fail fast, learn faster" mentality, aiming for a 20-30% success rate in your ideas and experiments. Continuously optimize our experimentation process, making it faster, more efficient, and more insightful
- Apply AI concepts to solve business problems, with a focus on rapid prototyping and iterative improvement
- Leverage SQL and data manipulation tools to work with complex datasets, exploring unconventional approaches
- Apply statistical methods, machine learning algorithms, and data visualization techniques to perform exploratory data analysis, embracing unexpected insights
- Build and interpret models using tools like PySpark and ML-Flow, constantly testing new approaches and parameters
- Write clean, well-documented code that facilitates collaboration and hence faster iteration
- Continuously evaluate and enhance existing models, viewing each iteration as an opportunity to learn and improve
Technical Skills
- Proficiency in rapidly prototyping and testing ideas using large, complex datasets and SQL
- Expertise in implementing and iterating on machine learning models and algorithms, with a focus on quick experimentation cycles
- Strong programming skills in Python and/or SQL, with an emphasis on writing code that facilitates easy modification and testing
- Experience in leveraging data visualization techniques to quickly interpret and communicate experimental results
- Ability to swiftly deploy and iterate on AI solutions in cloud environments
Soft Skills
- Passionate about experimentation and embracing failure, viewing setbacks as valuable learning opportunities
- Excellent written and verbal communication skills, able to articulate the value of experimentation and rapid iteration to stakeholders
- Thrives in ambiguity and uncertainty, comfortable with the idea that most experiments will not succeed; also designing good experiments is a crucial part of the R&D process
- Skilled at analyzing problems from multiple angles and generating a high volume of potential solutions
Preferred Qualifications
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (Tier 1 colleges are preferred)
- Minimum of 2 years of hands-on experience in data analysis, modeling, and AI solutions development
If you're passionate about leveraging data to drive business decisions and have a track record of delivering impactful AI solutions, we want to hear from you! Mode of Work - On-Site
Job Benefits
- GenAI experience – Work directly in the innovative field of GenAI,...
(Description truncated here for brevity but fully included internally)
Prodigal specializes in AI-native consumer finance solutions, providing an AI agent for servicing and collections that operates 24/7 across voice and digital channels. Their platform supports over 1 billion unique U.S. consumer interactions with a proprietary intelligence engine called PIE (Prodigal Intelligence Engine) that powers multiple applications to help lending and collections teams transition to AI-native operations.
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