Job Summary:
The Senior Associate, Valuation & Capital Market Analytics - Model Risk Management is responsible for execution and delivery of challenging Model Risk Management related engagements by performing Model Risk Management related activities such as designing effective challenge and validation of models, independent review of model documentation and governance, and writing high quality model validation reports.
Job Duties:
* Identifies and executes model risk across the model lifecycle including model development, implementation, and utilization
* Provides independent review by and serving as the subject matter expert executing against the model validation of models (Credit, Market, Forecasting, etc.) compliant with supervisory guidance on Model Risk Management policies and procedures, regulatory guidance, and industry leading practice
* Designs specific validation plans to provide "effective challenge" to models, including assessments of overall design, underlying theoretical approaches, data quality and controls, model specification and estimation, development testing, implementation, use, and approvals
* Provides effective challenge to the model design and construction and conduct incremental analysis and testing as necessary
* Identifies model limitations and ensures the appropriate remediation actions are in place and monitored
* Writes high-quality validation documentation that satisfies the client's internal model approval functions, audit requirements, and regulatory standards
* Communicates model validation conclusions to BDO internal senior management and relevant project stakeholders
* Other duties as required
Supervisory Responsibilities:
* Supervises and trains Associate validators on model validation processes
Qualifications, Knowledge, Skills and Abilities:
Education:
* Undergraduate degree in Mathematics, Econometrics, Statistics, Financial Engineering, or Quantitative Finance, required
* Master's degree, preferred
Experience:
* Two (2) years or more of relevant work experience (Model Risk Management), required
* Familiarity with Data Science, Artificial Intelligence / Machine Learning, Modeling Techniques, required
* Knowledge of data management fundamentals and data storage principles, required
* Strong analytical and quantitative skills to understand, validate and challenge models effectively, preferred
* Understanding of financial instrument valuation concepts, preferred
* Strong analytical and computer skills including experience with quantitative analysis technical tools and techniques, preferred
* Ability to explain difficult modeling and statistical concepts to diverse audiences and to experts at various clients, preferred
* Candidate needs to be comfortable providing technical assistance and modeling expertise to non-technical clients and internal teams, preferred
* Provide recommendations for improved and enhanced model efficiency to clients, preferred
* Exercise professional judgment on engagements by providing proactive solutions and recommendations, preferred
* Strong writing and verbal skills, preferred
* Demonstrate leadership skills, preferred
* Build and broaden industry knowledge to support organization and function initiatives by taking advantage of local and national training programs, preferred
* Ability to multi-task and communicate effectively with clients and staff in a consultative setting, preferred
License/Certifications:
* PhD, CPA, CIA, CFA, CA, CCA, CMA, CAIA or FRM certifications, preferred
Software / Technology:
* Proficient in the use of Microsoft Office Suite, specifically Excel, PowerPoint, and Word, required
* Experience in Programming skills languages such as in R\, SAS\, Python or other related programming languages, preferred
Language:
* N/A
Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate's qualifications, experience, skills, and geography.
National Range: $85,000 - $100,000
Maryland Range: $85,000 - $100,000
NYC/Long Island/Westchester Range: $85,000 - $100,000
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