Senior Data Scientist

$130,000-$185,000 Base Salary, Position eligible for additional incentives including bonus, 401k match, health and welfare benefits.

Hybrid work based in NYC.

National Funding (NF) is creating a new, state-of-the-art digital lending company, smallbusinessloans.com (SBL). SBL will launch fully digital lending offering targeted to SMBs seeking an automated loan experience. The company will differentiate itself from competitors via superior technology, risk management, data science, a fully digital UI, and a customer-first experience that emphasizes ease of use, fairness and transparency in pricing, and recognition of customer loyalty.

In order to maximize speed-to-market and efficiency, SBL intends to leverage the availability state-of-the art technology service providers and platforms. At the same time, SBL will build a robust set of modules around these platforms that will serve to differentiate SBL’s offerings in the marketplace and to its customers.

Position Summary:

The Senior Data Scientist role is a senior member of the Data Science team with broad responsibilities that span the scope of the Data Science team. The ideal candidate has extensive experience building risk models (credit and fraud) for scoring risk of personal and small business entities in a small business lending product environment. The ideal candidate will be a thought leader in helping design, develop, implement, and manage key risk models and leverage expertise in machine learning and statistics to achieve exceptional results.

The ideal candidate can identify objectives, scope requirements, and determine approaches to solution development independently. The candidate is able to apply advanced mathematical and statistical techniques (e.g. GBM, logistic regression, cluster analysis, neural networks, independence testing, etc..) to further results and develop organizational capabilities needed to fully exploit data as an asset.

Major Responsibilities:

• Manipulate structured and unstructured datasets from disparate sources
• Perform data processing, integration, cleansing, descriptive analysis, visualization, and reporting
• Develop, document, monitor, and improved machine learning models for credit assessment, fraud detection, and other relevant customer lifecycle models
• Performs advanced analytics (statistical and predictive analytics, machine learning modeling, etc.) to provide actionable insights that improve business outcomes and minimize risk
• Apply data analysis and modeling techniques to support business decisions
• Hands on role in deploying models and tracking performance metrics
• Implements projects from inception to completion, managing timelines and resources independently to deliver expected outcomes.
• Engage stakeholders to understanding business requirements (compliance, engineering, product, marketing, etc.)
• Provides consultation to business leaders and other stakeholders on how to leverage analytics insights and build strategies around analytics
• Other duties as assigned.

Knowledge, Skills and Abilities Required:

• 4 years developing credit models for small business lending

• Bachelor’s degree in computer science, engineering, mathematics, statistics, or a similar quantitative field
• 6 years of relevant work experience
• Fluency in programming languages such as R, Python, SQL.
• Experience developing supervised and unsupervised machine learning algorithms
• Proficiency in working with SQL databases
• Strong programming practices utilizing version control systems (e.g. Git)
• Attention to detail and strong communication skills across technical and non-technical audience
• Extensive experience working with Python data science libraries
• Experience with Tableau and/or Looker

Experienced Preferred:

• 10 years of relevant work experience
• MS degree in a quantitative field such as mathematics, statistics, information systems, computer engineering or similar quantitative field
• Experience developing advanced models (default prediction, revenue forecasting, response prediction, etc.) in multiple functional areas (credit, fraud, marketing, etc.)
• Extensive experience developing credit models with GBM and Logistic Regression
• Experienced working withing Google Cloud AI tools
• Experience in applying statistical techniques to draw causal inferences in both experimental and non-experimental situations
• Experience leading end-to-end data science projects
• Experience mentoring other data scientists

National Funding is an Equal Opportunity Employer.