Data Scientist I/ Ii - Model Ops

CompanyFederal Reserve Bank of Cleveland

The Federal Reserve Bank of Cleveland is part of the nation’s central bank and we’ve provided many opportunities for professional growth during our history.

We’ve been named “One of Northeast Ohio’s Best Places to Work” by North Coast 99. This prestigious award honors organizations with outstanding employment practices, including compensation, benefits, training, recruitment, retention, community services, and employee communications.

Our People Make the Difference! The Federal Reserve Bank of Cleveland is seeking innovative thinkers with vision to build the framework that will carry the Bank into the future.

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This position requires access to confidential supervisory information and/or FOMC information, which is limited to "Protected Individuals" as defined in the U.S. federal immigration law. Protected Individuals include, but are not limited to, U.S. citizens, U.S. nationals, and U.S. permanent residents who either are not yet eligible to apply for naturalization or who have applied for naturalization within the requisite timeframe. Candidates who are not U.S. citizens or U.S. permanent residents may be eligible for the information access required for this position and sponsorship for a work visa, and subsequently for permanent residence, if they sign a declaration of intent to become a U.S. citizen and meet other eligibility requirements.

In addition, all candidates must undergo an enhanced background check and comply with all applicable information handling rules, and all non-U.S. citizens must sign a declaration of intent to become a U.S. citizen and pursue a path to citizenship.

The Advanced Analytics team in the Supervision & Regulation department strives to be data science innovators. We develop new models and metrics, using a wide range of vendor and internal datasets, to monitor risks in the banking sector and more generally promote a safe, sound, and fair financial system. For this role, we are looking for candidates who especially enjoy the engineering aspects of data science development, with experience in orchestrating data and model pipelines together for delivery as an end product. However, as a Data Scientist on our team, you will have the opportunity to work across all aspects of the analytics pipeline, from evaluating candidate datasets for use, applying last-mile data engineering, developing ML, NLP, or econometric models, creating data visualizations, and deploying models to front-end systems in a repeatable automated manner. If you are a technology professional looking to break into data science or a quant interested in growing your tech skills, this could be the role for you.

Essential Accountabilities

• Contributes to analytic projects through all stages of development, but is primarily responsible for deployment, monitoring, and maintenance of production models and tools.

• Has programming skills to transform large and complex datasets in a manner that is suitable for analysis and modeling.

• Visualizes and reports analytic findings using a variety of methods to promote understanding of key insights and actionable takeaways for both technical and non-technical audiences.

• Develops predictive models using machine learning, econometric modeling and data mining techniques to measure, assess and predict various measures of financial risk.

• Serve as a subject-matter expert in assessing artificial intelligence and information technology risk for FRS supervised firms with a focus on generative artificial intelligence, network controls, logical security, threat and vulnerability management, and resiliency at large, complex financial organizations.

• Delivers formal presentations, create analytical reports and executive summaries of findings.

Education and Experience

Data Scientist I

• Bachelor's degree in Data Science, Computer Science, or related field

• 5+ years of related work experience

• Or Preferred - Master's degree in Data Science, Computer Science, or related field

• 3+ years of related work experience

Data Scientist II

• Bachelor's degree in Data Science, Computer Science, or related field

• 7+ years of related work experience

• Or Preferred - Master's degree in Data Science, Computer Science, or related field

• 5+ years of related work experience

Knowledge and Skills Areas - Intermediate Level

• Experience with data science tools and compute platforms (e.g., AWS SageMaker, Databricks, Domino, Red Hat Enterprise Linux, Red Hat OpenShift)

• Experienced in application of advanced quantitative techniques in Data Science, Computer Science or related field

• Knowledge of banking and financial markets

• Experienced in Python programming, including developing Python Dash or Flask applications and FastAPIs

• Experience with machine learning and statistical programming using Python frameworks like Pandas, Scikit-learn, PyTorch, Hugging Face, NLTK, and Spacy

• Experience working with large data sets and data processing tools like SQL, Hadoop, Spark

• Experience with DevOps, ModelOps, and automation tools like Git, GitLab, DVC, Kubernetes

• Communication skills - both written and verbal. Ability to deliver presentations and draft publication-quality reports.

Physical Demands and General Working Conditions: Traditional office environment: Employees typically sit most of the day, work with a computer and may answer/respond to phone calls. Physical movement consists of walking for meetings, breaks, etc. Ability to lift items weighing approximately 20 pounds on a limited basis is required. Addendum as needed: Employees may be required to travel by car/air.

Full Time / Part TimeFull timeRegular / TemporaryRegularJob Exempt (Yes / No)YesJob CategoryAnalyticalWork ShiftFirst (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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