About Us:
Paytm is India’s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases. Paytm provides consumers with services like utility payments and money transfers, while empowering them to pay via Paytm Payment Instruments (PPI) like Paytm UPI. To merchants, Paytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks’ financial instruments. To further enhance merchants’ business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners.
Position Summary:
We are seeking a highly skilled and experienced Data Scientist who will build and own machine learning models with the end goal of mitigating risk across merchant and user journey while enhancing growth across different segments of our business.
You will work on developing classical machine learning as well deep learning models for Risk (fraud, credit and operational risk) use cases as well as building in-house foundation models for learning representation of entities like customers, merchants, devices etc. in our ecosystem. In this role you will work with a talented engineering and data science team to build and deploy models at scale. You will have the opportunity to apply and improvise over the latest breakthroughs in AI research from industry and academia and bring them into life with our data product offerings.
What does this include?
Design, build, evaluate and maintain ML/DL models to detect various types of risk mitigation problems while improving end user experience
Collaborate with product and analytics partners for business to ML problem formulation and align on key deliverables
End-to-end management of the entire lifecycle of the machine learning or deep learning project, from identifying objectives and preparing data to testing and validating models, calibrating them, monitoring and feedback loop.
Unsupervised learning methods to augment existing supervised models, or detect portfolio
anomalies
Requirements:
Have developed and deployed ML models at scale
Real time feature engineering pipeline and model development is a plus
Knowledge of classical ML models for classification and regression. Should have developed and deployed one such model from scratch. Know the trade off between choosing the techniques
Working knowledge on Sequential Neural NEtwork and Knowledge Graph representation learning using Graph Neural Network is a plus
Excellent understanding of ML/DL frameworks (Keras/Tensorflow/PyTorch etc.) and libraries (scikit-learn, etc.).
Excellent understanding of computer science fundamentals, data structures, and algorithms. Should have familiarity with object-oriented design methodology and application development in Python.
Familiar with Big Data related technologies to manage large volumes of complex data (SQL, pyspark). Knowledge of Scala is a plus
Passion to learn and build quick POC’s with state-of-the-art ML/DL algorithms.
Working experience of fraud risk is plus
BS in Computer Science or MS in Data Science discipline (or equivalent).
Why join us:
Because you get an opportunity to make a difference, and have a great time doing that
You are challenged and encouraged here to do stuff that is meaningful for you and for those we serve
You should work with us if you think seriously about what technology can do for people
We are successful, and our successes are rooted in our people's collective energy and unwavering focus on the customer, and that's how it will always be.
Compensation:
If you are the right fit, we believe in creating wealth for you.
With enviable 500 mn+ registered users, 21 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merchants – and we are committed to it.
India’s largest digital lending story is brewing here. It’s your opportunity to be a part of the story!
