Data Scientist

at  Federal Reserve Bank of St Louis

Company
Federal Reserve Bank of St. Louis
The Supervision, Credit and Learning Division of the Federal Reserve Bank of St. Louis oversees banking institutions and provides central bank services in the 8th District. The Supervision Division’s Digital Transformation Consulting (DTC) team helps solve business problems to inform business decisions by using data science techniques, such as statistical models and machine learning, to automate manual tasks, provide insights, increase efficiency, and build forecasting capabilities.
We are looking for a Data Scientist to work within the DTC team to conceive, design, and implement intelligent solutions for partners across a variety of subject matter domains. You will report to a manager and work onsite in the St. Louis office. DTC is a growing unit where team members participate in setting a strategic direction, market our products to potential clients, and communicate capabilities with stakeholders.

Responsibilities

• Transform raw data into data-driven insights, trends, and patterns, and recommendations through use of data science and analytics modeling and programing tools.
• Develop and implement a variety of machine learning solutions (classification, regression, clustering, reinforcement learning, natural language processing, GenAI) across a broad domain of financial and operational datasets.
• Partner with Data Engineering to set up technologies such as cloud environments, data pipelines, ensuring data quality, integrity, and accessibility.
• Work with cross-functional teams to understand business need and deliver actionable insights.
• Communicate findings and recommendations to a variety of technical and non-technical audiences, including written reports, visual presentations, and executive summaries.
• Continuously explore and evaluate new data sources and tools, and techniques to improve analysis and modeling capabilities.
• Collaborate with other data analytics teams across the System to implement solutions on an enterprise-wide basis.

Qualifications

• Bachelor’s degree in Statistics, Economics, Mathematics, Computer Science or other analytical/quantitative programs.
• 5 years applied experience in a professional setting, including 3 years of statistical modeling experience.
• Proficiency in programming languages such as R or Python, and database solution languages like SQL.
• Experience developing dashboards using RShiny, dash, and other data visualization tools.
• Hands on experience developing analytical tools. Experience working with targeting tools and databases.
• Excellent problem-solving skills and attention to detail.
• Experience deploying solutions to server and cloud platforms, including data security management.
• Candidates with less experience may be considered at a lower job grade or salary.

Total Rewards
Bring your passion and expertise, and we’ll provide the opportunities that will challenge you and propel your growth—along with a wide range of benefits and perks that support your health, wealth, and life.
Salary: 100,000 – 125,000

In addition to competitive compensation, we offer a comprehensive benefits package all brought together in a flexible work environment where you can find balance:

• Medical (4 options), Prescription, Dental (3 options), and Vision Insurance with no waiting period
• 401k/Thrift Plan with generous employer match
• Employer-funded Pension Plan
• Paid Vacation/Sick Time & Holidays
• Flexible Spending Accounts and Healthcare Spending Accounts
• Flexible Work Schedule available in most departments
• Life Insurance and Long Term Disability Insurance
• Tuition Reimbursement (undergraduate and graduate)
• Parental Leave
• Free onsite 24/7 Fitness Center including training classes, and locker room / shower facilities
• Onsite Cafeteria & Coffee Shop
• Additional Convenience Benefits, Discounts and More…

At the Federal Reserve Bank of St. Louis, we believe the Federal Reserve most effectively serves the American public by building a more diverse and inclusive economy. Our commitment to diversity and inclusion, at all levels of the organization, has been one of our core values for many years and remains strong as we continue enhancing our efforts. Learn more about Bank’s
culture
.
The Federal Reserve Bank of St Louis is an Equal Opportunity Employer.
This position requires access to confidential supervisory information (CSI) and/or Federal Open Market Committee (FOMC) information. Access to CSI and FOMC information is limited to U.S. citizens, lawful permanent residents, individuals who meet the definition of “protected individual” under 8 U.S.C. § 1324b(a)(3), and certain other nonimmigrants. All non-U.S. citizens authorized to access CSI and/or FOMC information must sign a declaration of intent to expeditiously become a U.S. citizen when eligible.
All employees who require access to CSI and/or FOMC information are subject to periodic background investigations and must comply with all applicable information handling policies.
Full Time / Part Time
Full time
Regular / Temporary
Regular
Job Exempt (Yes / No)
Yes
Job Category
Information Technology
Work Shift
First (United States of America)
The Federal Reserve Banks believe that diversity and inclusion among our employees is critical to our success as an organization, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.
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• Transform raw data into data-driven insights, trends, and patterns, and recommendations through use of data science and analytics modeling and programing tools.
• Develop and implement a variety of machine learning solutions (classification, regression, clustering, reinforcement learning, natural language processing, GenAI) across a broad domain of financial and operational datasets.
• Partner with Data Engineering to set up technologies such as cloud environments, data pipelines, ensuring data quality, integrity, and accessibility.
• Work with cross-functional teams to understand business need and deliver actionable insights.
• Communicate findings and recommendations to a variety of technical and non-technical audiences, including written reports, visual presentations, and executive summaries.
• Continuously explore and evaluate new data sources and tools, and techniques to improve analysis and modeling capabilities.
• Collaborate with other data analytics teams across the System to implement solutions on an enterprise-wide basis