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Sr Quantitative Fin Analyst

Charlotte, North Carolina;

Job Description:

The Senior Quantitative Finance Analyst will be a key leader in the Model Risk Management focusing on machine learning models. The role is especially designed to provide both thought leadership and hands-on expertise in methodology, techniques, and processes in applying statistical and machine learning models to identify suspicious money laundering activities. These models include, but not limited to, Regression, Gradient Boosting Tress, Random Forest, and Artificial Neural Network.


The position will be responsible for
• Performing all model validation tasks including but not limited to independent model validation, annual model review, ongoing monitoring report review, required action item review, and peer review.
• Conducting all administrative and governance activities such as model identification, model approval, breach actions, extension assessments, and system of records, to manage model risk.
• Providing hands-on leadership for projects pertaining to statistical modeling and machine learning approaches; and providing methodological, analytical, and technical support to effectively challenge and influence the strategic direction and tactical approaches of these projects.
• Communicating and working directly with relevant modeling teams and their corresponding Front Line Units; and if needed, communicating and interacting with the third line of defense (e.g. internal audit) as well as external regulators and governance agents.
 

Required skills:
The successful candidate should be a seasoned modeler or validator and meet the following requirements:
• Conducted complete and rigorous independent development and/or validation of models.
• At least 3-years of work experience at another financial services firm in quantitative research, model development, and/or model validation.
• PhD in mathematics, statistics, computer science, and/or engineering, with a solid knowledge of the banking and finance industry; or possess a graduate degree in finance and/or economics with strong quantitative skills.
• Proficient in SAS and Python, and experienced in ML packages (e.g. sklearn, tensorflow, Xgboost)
• Strong knowledge of financial, mathematical and statistical theories and practices, and a deep understanding of the modeling process, model performance measures, and model risk.
• Strong written and verbal communication skills

Job Band:

H4

Shift: 

1st shift (United States of America)

Hours Per Week:

40

Weekly Schedule:

Referral Bonus Amount:

0

Job Description:

The Senior Quantitative Finance Analyst will be a key leader in the Model Risk Management focusing on machine learning models. The role is especially designed to provide both thought leadership and hands-on expertise in methodology, techniques, and processes in applying statistical and machine learning models to identify suspicious money laundering activities. These models include, but not limited to, Regression, Gradient Boosting Tress, Random Forest, and Artificial Neural Network.


The position will be responsible for
• Performing all model validation tasks including but not limited to independent model validation, annual model review, ongoing monitoring report review, required action item review, and peer review.
• Conducting all administrative and governance activities such as model identification, model approval, breach actions, extension assessments, and system of records, to manage model risk.
• Providing hands-on leadership for projects pertaining to statistical modeling and machine learning approaches; and providing methodological, analytical, and technical support to effectively challenge and influence the strategic direction and tactical approaches of these projects.
• Communicating and working directly with relevant modeling teams and their corresponding Front Line Units; and if needed, communicating and interacting with the third line of defense (e.g. internal audit) as well as external regulators and governance agents.
 

Required skills:
The successful candidate should be a seasoned modeler or validator and meet the following requirements:
• Conducted complete and rigorous independent development and/or validation of models.
• At least 3-years of work experience at another financial services firm in quantitative research, model development, and/or model validation.
• PhD in mathematics, statistics, computer science, and/or engineering, with a solid knowledge of the banking and finance industry; or possess a graduate degree in finance and/or economics with strong quantitative skills.
• Proficient in SAS and Python, and experienced in ML packages (e.g. sklearn, tensorflow, Xgboost)
• Strong knowledge of financial, mathematical and statistical theories and practices, and a deep understanding of the modeling process, model performance measures, and model risk.
• Strong written and verbal communication skills

Shift:

1st shift (United States of America)

Hours Per Week: 

40

Learn more about this role

Full time

JR-21069312

Band: H4

Manages People: No

Travel: No

Manager:

Talent Acquisition Contact:

Taylor Pitre

Referral Bonus:

0