Job description
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.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.