At LendingPoint, we believe that everyone deserves to feel the power of possibilities. As an online fintech company, we’ve created advanced consumer, small business, and merchant point-of-sale lending solutions to unlock access to affordable loans and empower those working to build their financial potential. By creating technology that sees your potential, we’re driving a better lending and borrowing experience by finding more reasons to say “yes.”
More than just a job, LendingPoint is an exciting career choice where you’ll bring your expertise and experience to a talented team focused on big data.
Are we speaking about you? Then keep reading.
What’s In It For You?
- Competitive Base Salary
- Excellent Benefits Package That Includes: Medical/Dental/Vision, 401(k) match, Paid Holidays, and more!
- Team Oriented Fast-Paced Fun Environment
- Dedicated and experienced Management Team
- On-going training and investment in our employees
What You’ll Do Day to Day:
We are looking for a senior data scientist who shares our vision of building sophisticated risk models to advance financial inclusion and access to responsible credit. In this role you will help develop best-in-class credit risk, fraud, income verification, and marketing response models. The candidate is expected to have strong data analytics skills, statistical background, machine learning knowledge, and a passion for solving problems in innovative ways to drive business results.
ESSENTIAL JOB FUNCTIONS:
- Assist in building industry-leading credit, fraud, and pricing models to drive real-time lending decisions for hundreds of thousands of borrowers every month.
- Leverage advanced machine learning techniques and complex data sources such as credit bureau information at large scale to help build sophisticated credit and fraud models.
- Partner with product and engineering teams to deploy models into production environment.
- Evaluate new statistical and modeling approaches and alternate data sources to drive better credit decisions.
- Optimize complex SQL programs for speed and efficiency.
- Perform data wrangling, ETL, and data exploration tasks.
MINIMUM QUALIFICATIONS:
- Bachelor’s in a quantitative field (e.g., Mathematics, Data Science, Statistics, Economics, Finance, etc.). Master’s degree preferred.
- 2+ years’ experience in fintech or financial services applying statistical and machine learning predictive techniques.
- Expert knowledge in one of the statistical programming languages such as Python or R, and database languages such as SQL
- Experience using GCP and/or Hadoop systems for distributed analytics and data processing.
- Ability to work in fast-paced environment.