Data Scientist, Risk Management 946339

We are:

We are a fast growing Data Science team. We value innovation and collaboration. Our team is working with vital analytics to ensure we are within the guidelines for banking regulations and ensuring the continued growth of the bank.

You will:

Perform statistical analysis to determine Fair Lending regulatory risks associated with us and our Marketplace Lending partners in underwriting, pricing, and servicing.

Gather and report on data necessary for fair lending assessments, data availability, and data quality.

Present data and analysis in a clear and concise manner allowing the audience to quickly understand the results and recommendations so they can make informed data driven decisions.

Collaborate with various partners to provide a holistic view of the analysis. Measure and monitor results of applied recommendations and present adjustments.

Develop insightful and compelling summary reporting and dashboards for management and business line partners.

Developing analytical methods and models that assess the Fair Lending regulatory risks of new and existing lending products.

Work regularly with the US team on the East Coast and be available until 19:30/20:00 4 days a week.

You are:

You’re the kind of person that loves to get things done, collaborate with colleagues overseas, and are interested in joining a highly profitable fast-growing fintech company.

You are looking to get onto the ladder leading up to becoming a Data Scientist.

You are detail oriented with an analytical, logical way of thinking, and are passionate about making data driven decisions.

You are ready to put the work in to learn from the best. You have worked on SQL and have had some exposure to programming.

You have:

• 3+ years of related work experience
• Strong programming skills in Python
• Strong knowledge of databases and related languages/tools such as SQL
• Experience with AWS, Glue, Athena and machine learning tools, such as Sagemaker
• Experience of machine learning and statistical modeling methods
• Familiarity with financial services, particularly the loan business
• Bachelor’s in economics, finance, statistics, computer science or a related quantitative field
• It's a bonus if you have: some knowledge of the use of statistical analysis related to anti-discrimination laws such as fair lending, programming skills in SAS, familiarity with adversarial debiasing techniques

Please send CV to [email protected]