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Sr. Quantitative Model Analyst
Career Insights for Data Scientist
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Scorecard
Based on Ohio data
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What they do
A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
$105,235 / year median in Ohio
+16% projected growth
Job Description
Job Description An employer is seeking a full time employee for a hybrid Quantitative Risk Analyst role in Cincinnati.
This person will:
Independently leads and assists activities related to managing and mitigating model risks, by independently performing validations, monitoring governance, and providing guidance and expertise related to models used by the Bank. The Senior Analyst collaborates with various stakeholders to ensure the accuracy, reliability, and regulatory compliance of models used for pricing, risk measurement, and decision-making processes.
Principal Duties and Responsibilities:
•
Model Validation and Governance:
Independently perform validation and governance efforts related to Bank models. Conduct comprehensive assessments of model accuracy, reliability, and robustness. Independently perform model validation activities, including reviewing model assumptions, methodologies, and implementation. Identify limitations, weaknesses, or gaps in models and propose enhancements or alternative approaches.
•
Model Risk Management Framework:
Contribute to the development and enhancement of the bank's model risk management framework, policies, and procedures. Support the implementation and management of model risk management processes, including model inventory, model change management, and ongoing model monitoring.
•
Regulatory Compliance:
Coordinate with key stakeholders to ensure compliance with regulatory model risk requirements (FHFA
AB 2013-07
;
FHFA AB 2022-03
).
•
Risk Identification and Measurement:
Identify and assess the risks associated with financial models, including model errors, biases, and limitations.
•
Model Documentation and Reporting:
Prepare comprehensive model validation reports, documenting the validation process, findings, and recommendations.
•
Collaboration and Leadership:
Collaborate with key stakeholders to provide guidance and expertise in support of a sound model risk management environment at the Bank. Provide guidance and mentorship to junior members of the model risk management team.
•
Continuous Improvement and Innovation:
Stay abreast of emerging trends, industry best practices, and technological advancements in model risk management. Identify opportunities for process optimization, automation, and efficiency gains within the model risk management function and ERM department.
• Performs additional duties as requested by management. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.
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Insight Global's Workforce Privacy Policy:
https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements 7+ years of experience in Model Risk Management, Model Validation, or Quantitative Risk (Experience validating or developing financial models within a bank, financial institution, consulting firm, regulator, or rating agency.) Experience with pricing, risk measurement, forecasting, or decisioning models. Quantitative Background Degree in Finance, Financial Engineering, Economics, Mathematics, Statistics, or related field. Experience using Python, R, MATLAB, SAS, or similar tools for model analysis, validation, and testing. Excellent Communication & Stakeholder Management (Ability to explain model findings, limitations, and risks to both technical and non-technical audiences) Ph.D. or Masters in a relevant discipline
Benefits
- Dental Insurance