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 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
