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Machine Learning (ML)The role is with a Fintech Credit Card company based in Pune within the Decision Science team. (OneCard )
About
Credit cards haven't changed much for over half a century so our team of seasoned bankers, technologists, and designers set out to redefine the credit card for you - the consumer. The result is OneCard - a credit card reimagined for the mobile generation. OneCard is India's best metal credit card built with full-stack tech. It is backed by the principles of simplicity, transparency, and giving back control to the user.
The Engineering Challenge
“Re-imaging credit and payments from First Principles”
Payments is an interesting engineering challenge in itself with requirements of low latency, transactional guarantees, security, and high scalability. When we add credit and engagement into the mix, the challenge becomes even more interesting with underwriting and recommendation algorithms working on large data sets. We have eliminated the current call center, sales agent, and SMS-based processes with a mobile app that puts the customers in complete control. To stay agile, the entire stack is built on the cloud with modern technologies.
Purpose of Role :
- Develop and implement the collection analytics and strategy function for the credit cards. Use analysis and customer insights to develop optimum strategy.
CANDIDATE PROFILE :
- Successful candidates will have in-depth knowledge of statistical modelling/data analysis tools (Python, R etc.), techniques. They will be an adept communicator with good interpersonal skills to work with senior stake holders in India to grow revenue primarily through identifying / delivering / creating new, profitable analytics solutions.
We are looking for someone who:
- Proven track record in collection and risk analytics preferably in Indian BFSI industry. This is a must.
- Identify & deliver appropriate analytics solutions
- Experienced in Analytics team management
Essential Duties and Responsibilities :
- Responsible for delivering high quality analytical and value added services
- Responsible for automating insights and proactive actions on them to mitigate collection Risk.
- Work closely with the internal team members to deliver the solution
- Engage Business/Technical Consultants and delivery teams appropriately so that there is a shared understanding and agreement as to deliver proposed solution
- Use analysis and customer insights to develop value propositions for customers
- Maintain and enhance the suite of suitable analytics products.
- Actively seek to share knowledge within the team
- Share findings with peers from other teams and management where required
- Actively contribute to setting best practice processes.
Knowledge, Experience and Qualifications :
Knowledge :
- Good understanding of collection analytics preferably in Retail lending industry.
- Knowledge of statistical modelling/data analysis tools (Python, R etc.), techniques and market trends
- Knowledge of different modelling frameworks like Linear Regression, Logistic Regression, Multiple Regression, LOGIT, PROBIT, time- series modelling, CHAID, CART etc.
- Knowledge of Machine learning & AI algorithms such as Gradient Boost, KNN, etc.
- Understanding of decisioning and portfolio management in banking and financial services would be added advantage
- Understanding of credit bureau would be an added advantage
Experience :
- 4 to 8 years of work experience in core analytics function of a large bank / consulting firm.
- Experience on working on Collection analytics is must
- Experience on handling large data volumes using data analysis tools and generating good data insights
- Demonstrated ability to communicate ideas and analysis results effectively both verbally and in writing to technical and non-technical audiences
- Excellent communication, presentation and writing skills Strong interpersonal skills
- Motivated to meet and exceed stretch targets
- Ability to make the right judgments in the face of complexity and uncertainty
- Excellent relationship and networking skills across our different business and geographies
Qualifications :
- Masters degree in Statistics, Mathematics, Economics, Business Management or Engineering from a reputed college
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