Data Science – Senior Data Scientist ( Model Governance )
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 Wallet, Paytm UPI, Paytm Payments Bank Netbanking, Paytm FASTag and Paytm Postpaid - Buy Now, Pay Later. 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.
About the Role:
We are seeking a highly motivated and experienced professional with expertise in credit lending model development, validation, and monitoring. The ideal candidate will be an expert in Python, PySpark, and SQL, with preferred expertise in AWS services such as EMR and S3.
Requirements:
3-6 years of experience in credit risk model development, validation, and monitoring.
Expert proficiency in one of the programming languages Python/PySpark for data manipulation, analysis, and modeling tasks.
Working knowledge in SQL.
Basic understanding of AWS services, particularly EMR and S3 for data processing and storage will be preferred.
Strong understanding of statistical analysis and machine learning algorithms.
Knowledge of credit risk assessment and scoring methodologies.
Excellent problem-solving and analytical skills.
Effective communication and collaboration abilities for working within cross-functional teams.
Demonstrated ability to take initiatives and work independently in a proactive manner.
Be a brand ambassador for Paytm – Stay Hungry, Stay Humble, Stay Relevant!
Expectations/Responsibilities:
Collaborate with stakeholders to support credit lending model development, validation, and monitoring initiatives.
Take initiatives in leading and assisting in the validation of credit lending models, ensuring compliance with regulatory guidelines and predefined metrics.
Implement governance controls to maintain compliance with internal and external policies.
Proactively contribute to the definition and implementation of data-driven strategies for credit lending.
Monitor and assess model performance, accuracy, and effectiveness on an ongoing basis.
Conduct exploratory data analysis and assist in preprocessing large datasets for model development.
Work closely with data scientists to interpret and communicate model results, providing actionable insights and recommendations to stakeholders.
Stay updated with the latest developments in data science, credit risk modeling techniques, and industry best practices.
Take proactive measures to document all aspects of model development, validation, monitoring, and governance control processes.
Smart thinking and clear communication
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!
This job is already closed and no longer accepting applicants, sorry.
