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Your day to day
In your day to day role you will
Mine complex data covering a wide range of information (from user profiles to transaction details); design/maintain critical US Pay Later metadata and dashboards that drive key business insights and decisions
Document data pipeline processes / data flows and design scalable framework for data quality checks and validation processes to ensure accuracy and consistency
Collaborate with Pay Later Risk Partners like Policy Owners, Data Engineers, Product Owners, SLOD / Governance, Fraud Policy, Collections, etc. ensuring smooth communication of business metrics
Drive US Pay Later data enhancement initiatives and communicate status of the initiatives to leadership at regular intervals
Carry out independent research by applying advanced statistical techniques to generate insights and solve risk problems that involve classification, clustering, pattern analysis, sampling, simulations, etc.
Trouble shooting any data, system and flow challenges while maintaining flawless data availability
What do you need to bring-
Bachelor’s degree or higher in a quantitative field such as Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline.
Prior experience in lending, credit risk management, or related field (preferred)
2+ years post-college working experience within a data-mining, quantitative research or analytics organization.
Must be an intuitive, organized analytical thinker, with the ability to perform detailed analysis.
Strong written, oral, and interpersonal skills a must including the ability to explain and/or present analysis.
Must have good business judgment with demonstrated ability to think creatively and strategically.
Aptitude and willingness to roll-up the sleeves and get involved in the details.
Proficiency in SQL, SAS, Python and visualization tools like Tableau, Qlikview, etc.
Our Benefits:
Any general requests for consideration of your skills, please
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