
10,000+ employees
Founded 1857
🏦 Banking
💸 Finance
💳 Fintech
💰 Post-IPO Equity on 2013-05
Banking • Finance • Fintech
Santander is a global retail banking group with a significant presence in Europe and the Americas. The company provides a range of financial services including consumer banking, asset management, private banking, and corporate and investment banking. Santander is committed to responsible banking, promoting diversity, equity, and inclusion, and supporting the green transition. With numerous customers worldwide, the bank focuses on financial inclusion and education as part of its corporate responsibility. Santander is listed on various stock exchanges and is involved in sponsorships like Formula 1, underscoring its brand presence and strategic partnerships.
🔥 24 minutes ago
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10,000+ employees
Founded 1857
🏦 Banking
💸 Finance
💳 Fintech
💰 Post-IPO Equity on 2013-05
Banking • Finance • Fintech
Santander is a global retail banking group with a significant presence in Europe and the Americas. The company provides a range of financial services including consumer banking, asset management, private banking, and corporate and investment banking. Santander is committed to responsible banking, promoting diversity, equity, and inclusion, and supporting the green transition. With numerous customers worldwide, the bank focuses on financial inclusion and education as part of its corporate responsibility. Santander is listed on various stock exchanges and is involved in sponsorships like Formula 1, underscoring its brand presence and strategic partnerships.
• Responsible for developing and maintaining sophisticated empirical models - including credit scoring models - for a nonprime auto lender • Summary and reporting of information to a variety of internal and external clients • Interact with many other departments to achieve overall company objectives • Participate in the construction of complex mathematical models – including credit origination, pricing and customer behavior scorecards • Develop underlying assumptions, theory, empirical evidence, and conceptual soundness of statistical and mathematical models • Apply statistical techniques to analyze trends and uncover risks and opportunities • Use internal and external data sources to create robust model development datasets • Ensure modeling projects are conducted in accordance with established company policies and mathematical modeling practices • Identify modeling needs and communicate them to the Director Quantitative Modeling • Assess department procedures for accuracy and completeness • Utilize data mining and statistical techniques to develop analytic insights, sound hypotheses, and informed recommendations • Encapsulate analytic findings into executive-level summary documents for senior management decision-making • Liaison with IT and other internal teams to define requirements and ensure timely and accurate delivery of data elements • Provide requisite information in support of independent model validation activities • Develop understanding of the firm’s operations and business practices • Support Model Validation and documentation of models in accordance with internal policies and U.S. Federal Reserve regulations
• Bachelor's Degree or equivalent work experience: Statistics, Economics, Operations Research, Applied Mathematics, or a related quantitative discipline required or equivalent experience • Master's Degree: Statistics, Economics, Operations Research, Applied Mathematics, or a related quantitative discipline required or equivalent experience. - Preferred • Ph.D.: Statistics, Economics, Operations Research, Applied Mathematics, or a related quantitative discipline required or equivalent experience - Preferred • 3+ Years Analytics in Financial Services Industry. - Required • 3+ Years Indirect subprime Auto Financial Services Industry experience. - Preferred • 3+ Years Prior experience developing credit scoring models preferred. - Preferred • Familiarity with logistic regression models, segmentation and variable reduction techniques, hypothesis testing, neural networks, design of experiments, ANOVA, decision trees, and linear regression • Prior experience working with credit bureau data strongly preferred • Prior experience using Python, or SAS, SQL • Demonstrated ability to use SQL and Python to extract data from multiple data sources • Demonstrated ability to merge, concatenate, and prepare extremely large datasets for statistical analysis and mathematical model development • Demonstrated ability to create complex pivot tables in MS Excel • Ability to effectively explain advanced mathematical concepts, techniques, and analyses to a business audience • Ability to translate analysis into a clear business plan • Strong written and verbal communication skills • Ability to maintain confidentiality
• Competitive salary • Fair and competitive rewards package • Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development opportunities
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