Job Description
This person is going to be the champion of data analytics and fraud detection at Zaakpay. He/She will shape Zaakpay's risk management capabilities and help keep chargeback losses in check. The core responsibilities would include
- Build transaction risk and account risk models from scratch
- Analyze models to optimize them and track portfolio performance
- Identify new data sources which provide strong identifiers of fraud
- Create fuzzy tools to identify new fraud trends
- Fine-tune existing risk models
Desired Skills & Experience
- *** Freshers need not apply ***
- 5+ years of strong experience in analyzing data and building statistical models
- Bachelors, Masters or PhD degree in Quantitative, Math, Stats, Engineering required
- Experienced user of at least 1 modeling tool such as SAS, SQL, Matlab, Perl
- Background in financial services or banking specifically in online fraud detection is a plus
- Work experience in Consumer Credit or eCommerce is also a plus
- Must be interested in web startups and an avid user of commerce websites globally
- Common sense approach to problem solving is expected
- Must be able to take risks
- Skills important but self-starter attitude very important
- Must be able to stick for one year minimum
- You must be aware of these terms: eCommerce, Credit Card Fraud, Online Fraud detection, Risk modeling, Chargeback, Loss rate
- You must be aware of these companies: Klarna, PayPal, Cybersource
Company Description
Zaakpay is a payments company based in New Delhi & Bangalore. Our aim is to solve the payment pain points for eCommerce in India. In terms of product, we are still at the foundation level and our aspiration is to build a skyscraper. So there is a lot of new product that needs to be built bottoms up.
Our founding team comes with significant background in payments and technology having worked with PayPal, HSBC, Intel, Nvidia, Intuit, Yahoo, Juniper, Ixigo, and MobiKwik. We are backed by the good folks at Sequoia Capital India. Come work with us at Zaakpay, we are hiring!
Job Description
This person is going to be the champion of data analytics and fraud detection at Zaakpay. He/She will shape Zaakpay's risk management capabilities and help keep chargeback losses in check. The core responsibilities would include
- Build transaction risk and account risk models from scratch
- Analyze models to optimize them and track portfolio performance
- Identify new data sources which provide strong identifiers of fraud
- Create fuzzy tools to identify new fraud trends
- Fine-tune existing risk models
Desired Skills & Experience
- *** Freshers need not apply ***
- 5+ years of strong experience in analyzing data and building statistical models
- Bachelors, Masters or PhD degree in Quantitative, Math, Stats, Engineering required
- Experienced user of at least 1 modeling tool such as SAS, SQL, Matlab, Perl
- Background in financial services or banking specifically in online fraud detection is a plus
- Work experience in Consumer Credit or eCommerce is also a plus
- Must be interested in web startups and an avid user of commerce websites globally
- Common sense approach to problem solving is expected
- Must be able to take risks
- Skills important but self-starter attitude very important
- Must be able to stick for one year minimum
- You must be aware of these terms: eCommerce, Credit Card Fraud, Online Fraud detection, Risk modeling, Chargeback, Loss rate
- You must be aware of these companies: Klarna, PayPal, Cybersource
Company Description
Zaakpay is a payments company based in New Delhi & Bangalore. Our aim is to solve the payment pain points for eCommerce in India. In terms of product, we are still at the foundation level and our aspiration is to build a skyscraper. So there is a lot of new product that needs to be built bottoms up.
Our founding team comes with significant background in payments and technology having worked with PayPal, HSBC, Intel, Nvidia, Intuit, Yahoo, Juniper, Ixigo, and MobiKwik. We are backed by the good folks at Sequoia Capital India. Come work with us at Zaakpay, we are hiring!
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