Data Engineer
Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Oct 20, 2026.
About YUBI
Yubi, formerly known as CredAvenue, is re-defining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfilment, and collection of any debt solution. At Yubi, opportunities are plenty and we equip you with tools to seize it.
In March 2022, we became India’s fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million.
In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest and trade bonds - all in one place. All 5 of our platforms shake up the traditional debt ecosystem and offer new ways of digital finance.
Yubi Loans - Term loans and working capital solutions for enterprises.
Yubi Invest - Bond issuance and investments for institutional and retail participants.
Yubi Pool- End-to-end securitisations and portfolio buyouts.
Yubi Flow - A supply chain platform that offers trade financing solutions.
Yubi Co.Lend - For banks and NBFCs for co-lending partnerships.
Currently, we have boarded over 4000+ corporates, 350+ investors and have facilitated debt volumes of over INR 40,000 crore.
Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment.
At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 650+ like-minded individuals today, who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come, join the club to be a part of our epic growth story.
Responsibilities:
As a part of the financial models team at CredAvenue, you will be part of a highly motivated DS team responsible for developing statistical & ML models, which requires reasonable understanding of the domain.
Work on state of the art data science models with predominantly structured data and work on problems such as fraud identification, network graphs, retail & institutional risk scorecards, portfolio construction & management and pricing models
You will also work closely with the Data Engineering team to capture structured data in the required databases, work with cross team stakeholders to gain domain expertise & obtain project buy-in and also work with DevOps & MLOps to get the models into production and develop ML pipelines to train, test and deploy models into production
You will be responsible for expediting the development lifecycle of various ML models. Along with ensuring that the model training and scoring in production scale properly for large volumes of data and user traffic. By ensuring the throughput of model training and response time of model scoring in production are controlled appropriately with relevant technologies and techniques.
Requirements
Expertise :
0-1 years of experience in data science/risk management /quantitative modeling / financial models
Domain knowledge on esp.financial data & risk, fraud & quant. models is an added advantage
Domain & Data Requirements
Prior experience in working with B2B data & building models for the same is an added advantage
Prior experience in using classic ML models for credit risk quantification (for retail or institutional)
Experience & willingness to handle cross team stakeholders to understand the domain & build accurate useful models.
Should be willing to identify project areas that are patentable & works towards it
Tech Requirements
Hands on experience in at least one programming language like Python & one querying language
Prior experience in code development using frameworks & technologies like Scikit, scipy etc.,.
Prior experience in working with databases like mongoDB, Postgres, SQL etc.,
Prior experience in working with cloud technologies, preferably AWS
Strong understanding of ML model life cycle i.e. development, training, testing & monitoring