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 fostering positive new customer experiences that inspire loyalty.
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 Lead 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 develop best-in-class credit risk, fraud, income verification, and marketing response models. The desired candidate will have a strong data science background, statistical expertise, machine learning knowledge, and a passion for solving problems in innovative ways to drive business results.
ESSENTIAL JOB FUNCTIONS:
Build 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, and alternative data sources, at large scale to build sophisticated credit and fraud models.
Collaborate 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.
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Optimize complex SQL programs for speed and efficiency.
MINIMUM QUALIFICATIONS:
Bachelor’s in a quantitative field (e.g., Mathematics, Data Science, Statistics, Economics, Finance, etc.). Master’s / PhD degree preferred.
4+ years’ experience in fintech or financial services applying advanced statistical and machine learning predictive techniques.
Expert knowledge in statistical programming languages such as Python, R, and database languages such as SQL
Knowledge of advanced statistical modeling, testing, data mining, ETL, and data science techniques.
Experience using GCP and/or Hadoop systems for distributed analytics and data processing.
Strong communication and interpersonal skills.
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.