Senior Data Scientist

February 26

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Oportun

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Oportun is a financial technology company that specializes in providing affordable personal loans and savings solutions. They are recognized as Bankrate's #1 app for saving money in 2024. Oportun offers personal loans ranging from $300 to $10,000 for various financial needs such as bills, repairs, and deposits, with quick funding and affordable payments. The company provides a unique app that helps users manage their loans and saves money intelligently. Oportun also focuses on financial education and offers tools like loan calculators and prequalification services, which do not impact credit scores. Although Oportun is not a bank, they ensure deposits are FDIC insured through partner banks.

Financial Services • Responsible Lending • Pre-Paid Debit Cards • Serving the Underbanked • Data Analytics

1001 - 5000 employees

Founded 2006

💳 Fintech

💸 Finance

📋 Description

•We are growing our world-class team of mission-driven, entrepreneurial Data Scientists who are passionate about broadening financial inclusion by untapping insights from non-traditional data. •Be part of the team responsible for developing and enhancing Oportun’s core intellectual property used in scoring risk for underbanked consumers that lack a traditional credit bureau score. •In this role you will be on the cutting edge working with large and diverse (i.e. data from dozens of sources including transactional, mobile, utility, and other financial services) alternative data sets and utilize machine learning and statistical modeling to build scores and strategies for managing risk, collection/loss mitigation, and fraud. •You will also drive growth and optimize marketing spend across channels by leveraging alternative data to help predict which consumers would likely be interested in Oportun’s affordable, credit building loan product.

🎯 Requirements

•A relentless problem solver and out of the box thinker with a proven track record of driving business results in a timely manner •Master’s degree or PhD in Statistics, Mathematics, Computer Science, Engineering or Economics or other quantitative discipline (Bachelor’s degree with significant relevant experience will be considered). •Hands on experience leveraging machine learning techniques such as Gradient Boosting, Logistic Regression and Neural Network to solve real world problems •3+ years of hands-on experience with data extraction, cleaning, analysis and building reusable data pipelines; Proficient in SQL, Spark SQL and/or Hive •3+ years of experience in leveraging modern machine learning toolset and programming languages such as Python •Excellent written and oral communication skills •Strong stakeholder management and project management skills •Comfortable in a high-growth, fast-paced, agile environment •Experience working with AWS EMR, Sage-maker or other cloud-based platforms is a plus •Experience with HDFS, Hive, Shell script and other big data tools is a plus