Frost

Compensation

Full Description

Job Description It’s about giving people a sense of security. Do you enjoy researching and extracting insights from data? Would others describe you as being reliable and resourceful? Do you have a background in statistics, mathematics, or finance? If so, being a Quantitative Risk Modeling Analyst II with Frost could be for you. At Frost, it’s about more than a job. It’s about having a flourishing career where you can thrive, both in and out of work. At Frost, we’re committed to fostering an environment that reflects our values and encourages team members to be the best they can be. In joining our adaptable, integrity-driven team, you’ll become part of Frost’s over 150-year legacy of providing unparalleled financial services. Who you are: As a Quantitative Risk Modeling Analyst II, you are our risk inspector. You’ll be responsible for applying data analytics to assist in drawing actionable insights into financial, transactional, demographic, and behavioral data. You will use your logical mind-set and organized approach to ensure work is appropriately documented and in compliance with State and Federal Laws and Regulations. You enjoy collaboration and look forward to collaborating with our compliance partners to identify ways to use data analytics. What you’ll do: Apply data analytics to assist in drawing actionable insights into complex business problems using financial, transactional, demographic and behavioral data Pull, clean, and aggregate data from sources across the Bank Ensure work is appropriately documented and in compliance with State and Federal Laws and Regulations Participate in collaboration efforts with Risk Management Teams to identify ways to use data analytics Maintain direct, ongoing communication with Risk Management Teams clients Always take action using Integrity, Caring, and Excellence to achieve all-win outcomes What you’ll need: Advanced (Ph.D. or Master’s) degree in quantitative analytics field such as mathematics, statistics, economics, or actuarial science 3+ years of experience developing statistical or machine learning models Mastery of statistics and numerical techniques Experience gathering and documenting requirements Experience writing model documentation Experience presenting analytical results Proficient in SQL Proficient in SAS, R or Python Proficiency in Microsoft computer applications (Excel, Word, Power Point) Excellent written and verbal communication skills Additional Preferred Skills: Experience with developing models in the financial services industry Our Benefits: At Frost, we care about your health, your family, and your future and strive to have our benefits reflect that. This includes: Medical, dental, vision, long-term disability, and life insurance 401(k) matching Generous holiday and paid time off schedule Tuition reimbursement Extensive health and wellness programs, including our Employee Assistance Program Referral bonus program + more! Since 1868, Frost has dedicated their expertise to provide exceptional banking, investment, and insurance services to businesses and individuals throughout Texas. Frost is one of the 50 largest U.S. banks by asset size and is a leader in banking customer satisfaction. At Frost, it’s about being part of something bigger. If this sounds like you, we encourage you to apply and see what’s possible at Frost. Our Most Important Relationship Starts Here Frost’s commitment to cultivate long-term relationships is one of the reasons we’re recognized as a premier employer in the financial services industry. To attract qualified professionals, we offer an environment that’s supportive of both your professional and personal goals by providing our employees with competitive salaries and an outstanding benefits package. Frost was named to Forbes magazine's list of the Best Employers. Frost is an Equal Opportunity Employer and does not discriminate on the basis of any protected trait, including sex, sexual orientation, gender identity, race, ethnicity, disability, or veteran status. View Employment Notices and Policies