CIT is a leading national bank focused on empowering businesses and personal savers with the financial agility to navigate their goals. CIT Group Inc. (NYSE: CIT) is a financial holding company with over a century of experience and operates a principal bank subsidiary, CIT Bank, N.A. (Member FDIC, Equal Housing Lender). The company's commercial banking segment includes commercial financing, community association banking, middle market banking, equipment and vendor financing, factoring, railcar financing, treasury and payments services, and capital markets and asset management. CIT's consumer banking segment includes a national direct bank and regional branch network. Discover more at cit.com/about.
The Quantitative Strategies group partners with all business areas and corporate functions within the organization for model development, quantitative research, business analytics, risk management and process enhancement. All members of the team work in close collaboration across multiple areas as business priorities dictate.
All team members are tasked with effectively following and adhering to applicable CIT policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.
The Quantitative Strategies team (QS) delivers model development, research and analysis to support CIT in 3 objectives:
• Building and supporting models for Commercial Banking.
• Building and supporting models for regulatory requirements.
• Build tools & process enhancements and identifying opportunities to automate parts of model development and contribute to infrastructure, tool, or process improvement to enable efficiencies on the team
• Ad-hoc quantitative support for other areas in the organization
• Advanced degree (Masters or PhD) required in Quantitative Finance, Applied Mathematics, Statistics, Engineering, or other quantitative-oriented disciplines.
• Demonstrated ability to effectively organize tasks, manage time, set priorities and deadlines
• Strong quantitative skills and analytical problem-solving ability required
• Ability to extract data, process data, and explore data.
• Advanced knowledge in statistical modeling, such as linear and logistic regression, time series, econometric models.
• Advanced programming skills in – Python, SQL, SAS. Experience with Power-BI or Tableau, and Excel.
• Knowledge of banking model related regulation (SR 11-7/OCC 2011-12) is preferred
• Excellent written and verbal communication and interpersonal skills, including the ability to reach the best possible results without compromising the work quality
• Team-work oriented and strong presentation skills
• Attention to details and highly organized.