Lead Data Scientist

LendingPoint, LLC

$120K — $150K *
US-AnywhereRemote in United States
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's in quantitative field; Master's/PhD preferred.
  • 4+ years in fintech or financial services with advanced statistical/machine learning techniques.
  • Expert in Python, R, and SQL programming.
  • Familiarity with advanced statistical modeling, testing, and data mining.
  • Experience with GCP and/or Hadoop for distributed data analytics.
  • Strong communication and interpersonal skills.
  • Ability to thrive in a fast-paced environment.

Responsibilities

  • Build credit, fraud, and pricing models for real-time lending decisions.
  • Utilize machine learning techniques and diverse data sources to construct models.
  • Collaborate with product and engineering teams to implement models.
  • Evaluate new statistical approaches and data sources for improved credit decisions.
  • Identify data-driven business opportunities across the organization.
  • Optimize SQL programs for enhanced performance and efficiency.

Benefits

  • Excellent medical, dental, and vision coverage.
  • 401(k) matching program.
  • Generous paid holidays.
  • Supportive and experienced management team.
  • Ongoing training and investment in employee growth.
  • Team-oriented and fast-paced work environment.
Full Job Description
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.

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