Data Scientist

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: 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 to 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 Be committed to diversity, equity, and inclusion, with a passion for promoting fairness and equality in lending practices You have: Proficient in Hebrew and English 3+ years of experience in data analysis, statistical modeling, and predictive analytics in the financial services industry, preferably in Fair Lending or credit decisioning Knowledge of advanced analytics and machine learning techniques including classification methods Experience with cloud-based platforms and technologies for analytics and machine learning Capable of working independently and collaboratively in fast-paced settings, managing multiple projects A Bonus Experience in Fair Lending analytics preferred Familiarity with regulations such as ECOA, FHA, HMDA, or similar financial protection laws preferred Background in financial services, lending products, or credit risk management preferred Knowledge of data visualization tools like Tableau and Power BI is a plus