Data Scientist

1 month ago

Noida, Uttar Pradesh, India Paytm Full time
About Us:
Paytm is a leading digital payments and financial services company in India, focused on driving consumers and merchants to its platform by offering various payment use cases. The company 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 other banks' financial instruments. To enhance merchants' business, Paytm offers commerce services through advertising and the Paytm Mini app store. By leveraging this platform, the company 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 to mitigate risk across merchant and user journeys while enhancing growth across different business segments. The successful candidate will work on developing classical machine learning and deep learning models for risk use cases, as well as building in-house foundation models for learning entity representations in our ecosystem. In this role, you will collaborate with a talented engineering and data science team to build and deploy models at scale. You will have the opportunity to apply and improve the latest breakthroughs in AI research from industry and academia, bringing them to life with our data product offerings.
Key Responsibilities:
  1. Design, build, evaluate, and maintain ML/DL models to detect various types of risk mitigation problems while improving end-user experience.
  2. Collaborate with product and analytics partners to formulate business-to-ML problems and align on key deliverables.
  3. Manage the entire lifecycle of machine learning or deep learning projects, from identifying objectives and preparing data to testing and validating models, calibrating them, monitoring, and feedback loops.
  4. Apply unsupervised learning methods to augment existing supervised models or detect portfolio anomalies.

Requirements:
  1. 4+ years of work experience as a Data Scientist.
  2. Developed and deployed ML models at scale.
  3. Real-time feature engineering pipeline and model development is a plus.
  4. Knowledge of classical ML models for classification and regression.
  5. Excellent understanding of ML/DL frameworks (Keras/Tensorflow/PyTorch etc.) and libraries (scikit-learn, etc.).
  6. Excellent understanding of computer science fundamentals, data structures, and algorithms.
  7. Familiarity with Big Data related technologies to manage large volumes of complex data (SQL, pyspark).
  8. Knowledge of Scala is a plus.
  9. Passion to learn and build quick POC's with state-of-the-art ML/DL algorithms.
  10. Challenging the norm, creative thinking, collaboration.
  11. Working experience of fraud risk is a plus.
  12. BS in Computer Science or MS in Data Science discipline (or equivalent).

Why Join Us:We offer a unique opportunity to make a difference and have a great time doing it. You will be challenged and encouraged to do meaningful work that benefits those we serve. Our successes are rooted in our people's collective energy and unwavering focus on the customer. We are a successful company, and our successes are a testament to our people's dedication and hard work. Learn more about the exciting work we do in Tech by reading our Engineering blogs.
Compensation:We believe in creating wealth for our employees. With over 500 million registered users, 21 million merchants, and a depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers and merchants. We are committed to this mission, and we invite you to be a part of it.

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