We develop cutting edge API driven banking solutions to some of the largest names.
We are:
The Data Science team, focused on Risk Management, our work is centered around compliance and due diligence, specifically Fair Lending and Anti Money Laundering by unmasking the bad guys and solving problems. Our team is working with vital analytics to ensure we are within the guidelines for banking regulations, managing the bank's exposure to loss and risk. Our team uses SAS, Python and various machine learning models to provide on-demand analysis.
You will:
- Manage a team that will design, develop, and implement predictive models, machine learning algorithms, and statistical techniques to assess fair lending risks and detect potential instances of discrimination
- Analyze large datasets and identify patterns, trends, and potential areas of concern related to Fair Lending practices
- Utilize advanced statistical methods to evaluate model performance, including model calibration, validation, and interpretation of results
- Collaborate with cross-functional teams to understand business requirements and develop data-driven solutions for Fair Lending compliance
- Develop and maintain of scalable data pipelines, data models, and analytical tools to support fair lending analysis and reporting activities
- Be committed to diversity, equity, and inclusion, with a passion for promoting fairness and equality in lending practices
- This position reports to the Fair Lending Data Science Manager
You have:
- 5+ years of experience in data analysis, statistical modeling, and predictive analytics within the financial services industry, preferably in Fair Lending or credit decisioning - Must
- Bachelor's degree in Statistics, Mathematics, Data Science, Economics, or a quantitative field. - Must (Advance degree an advantage)
- Proficient in Hebrew and English both written and verbal, sufficient for achieving consensus and success in a remote and largely asynchronous work environment - Must
- Strong knowledge of advanced analytics and machine learning techniques such as regression and classification algorithms, including linear and logistic regression, k-nearest neighbors, support vector machines (SVMs) and other techniques
- Experience working with cloud-based data platforms and technologies such as AWS and Sagemaker for scalable data analytics and machine learning
- Strong technical proficiency in data science tools and programming languages such as Python, R, SQL, with experience in developing predictive models and machine learning algorithms
- Experience working with large-scale datasets
- Ability to communicate findings and recommendations to stakeholders
- Strong problem-solving skills while paying attention to detail
- Strong project management skills, with the ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced, dynamic environment
- Ability to facilitate collaboration to achieve project goals
A Bonus:
- 2+ years of experience in a leadership or management role an advantage
- Familiarity with Fair Lending regulations such as the Equal Credit Opportunity Act (ECOA), Fair Housing Act (FHA), and Home Mortgage Disclosure Act (HMDA) preferred
- Experience in Fair Lending analytics preferred
- Knowledge of regulatory compliance frameworks and industry guidelines for fair lending risk management an advantage
- Experience with machine learning techniques, such as decision trees, random forests, or gradient boosting an advantage
- Experience with data visualization tools such as Tableau, Power BI an advantage
