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Data Scientist I

Employer
Bank of America Merrill Lynch
Location
Charlotte, USA
Salary
Competitive
Closing date
Oct 7, 2021

View more

Job Function
Other
Industry Sector
Finance - General
Employment Type
Full Time
Education
Bachelors
Job Description:

Candidate will assist model development groups with review and remediation of model development documentation prior to validation submission.
  • Review model development documentation, identify gaps against the current model development required standards, and determine action items to remediate gaps
  • Communicate findings to model development teams
  • When required, work on champion model review and potential re-development/optimization and/or challenger model development
  • Track remediation progress
  • Liaison with model development and model risk management teams
  • Hands on role in tracking and advising on post deployment ongoing monitoring

Required Skills
  • 5+ years of hands on model risk management or banking model development experience.
  • Familiarity with model risk management standards and regulation (e.g., SR 11-7)
  • Attention to detail
  • Good communication skills.
  • Ability to work across multiple threads.
  • Good analytical skills to breakdown requirements and establish remediation plans.
  • Bachelor's Degree required (in quantitative field preferred)

Preferred Skills
  • Familiarity with machine learning techniques and algorithms.
  • Experience in at least one of the following: Python, SAS, Java.
  • Chartered Financial Analyst (CFA), Financial Risk Manager (FRM), Project Management Professional (PMP) or history of AI/ML related journal publications.
  • Master's Degree in Statistics, Mathematics, Data Science, Engineering, Computer Science, Economics, or related quantitative field.


Required Technical Skillsets
  • Quantitative skills applied to modelling
  • Hands on experience with using machine learning techniques and algorithms and getting them to production (statistical models, ensemble and deep learning models).
  • Previous data science related work experience and domain expertise within the banking/financial sector
  • Strong theoretical understanding behind ML/AI modelling techniques and algorithms
  • Statistical computer languages (Python (preferred), R SAS, etc.)


Job Band:
H5

Shift:
1st shift (United States of America)

Hours Per Week:
40

Weekly Schedule:

Referral Bonus Amount:
0
Job Description:

Candidate will assist model development groups with review and remediation of model development documentation prior to validation submission.
  • Review model development documentation, identify gaps against the current model development required standards, and determine action items to remediate gaps
  • Communicate findings to model development teams
  • When required, work on champion model review and potential re-development/optimization and/or challenger model development
  • Track remediation progress
  • Liaison with model development and model risk management teams
  • Hands on role in tracking and advising on post deployment ongoing monitoring

Required Skills
  • 5+ years of hands on model risk management or banking model development experience.
  • Familiarity with model risk management standards and regulation (e.g., SR 11-7)
  • Attention to detail
  • Good communication skills.
  • Ability to work across multiple threads.
  • Good analytical skills to breakdown requirements and establish remediation plans.
  • Bachelor's Degree required (in quantitative field preferred)

Preferred Skills
  • Familiarity with machine learning techniques and algorithms.
  • Experience in at least one of the following: Python, SAS, Java.
  • Chartered Financial Analyst (CFA), Financial Risk Manager (FRM), Project Management Professional (PMP) or history of AI/ML related journal publications.
  • Master's Degree in Statistics, Mathematics, Data Science, Engineering, Computer Science, Economics, or related quantitative field.


Required Technical Skillsets
  • Quantitative skills applied to modelling
  • Hands on experience with using machine learning techniques and algorithms and getting them to production (statistical models, ensemble and deep learning models).
  • Previous data science related work experience and domain expertise within the banking/financial sector
  • Strong theoretical understanding behind ML/AI modelling techniques and algorithms
  • Statistical computer languages (Python (preferred), R SAS, etc.)


Job Band:
H5

Shift:
1st shift (United States of America)

Hours Per Week:
40

Weekly Schedule:

Referral Bonus Amount:
0
Job Description:

Candidate will assist model development groups with review and remediation of model development documentation prior to validation submission.
  • Review model development documentation, identify gaps against the current model development required standards, and determine action items to remediate gaps
  • Communicate findings to model development teams
  • When required, work on champion model review and potential re-development/optimization and/or challenger model development
  • Track remediation progress
  • Liaison with model development and model risk management teams
  • Hands on role in tracking and advising on post deployment ongoing monitoring

Required Skills
  • 5+ years of hands on model risk management or banking model development experience.
  • Familiarity with model risk management standards and regulation (e.g., SR 11-7)
  • Attention to detail
  • Good communication skills.
  • Ability to work across multiple threads.
  • Good analytical skills to breakdown requirements and establish remediation plans.
  • Bachelor's Degree required (in quantitative field preferred)

Preferred Skills
  • Familiarity with machine learning techniques and algorithms.
  • Experience in at least one of the following: Python, SAS, Java.
  • Chartered Financial Analyst (CFA), Financial Risk Manager (FRM), Project Management Professional (PMP) or history of AI/ML related journal publications.
  • Master's Degree in Statistics, Mathematics, Data Science, Engineering, Computer Science, Economics, or related quantitative field.


Required Technical Skillsets
  • Quantitative skills applied to modelling
  • Hands on experience with using machine learning techniques and algorithms and getting them to production (statistical models, ensemble and deep learning models).
  • Previous data science related work experience and domain expertise within the banking/financial sector
  • Strong theoretical understanding behind ML/AI modelling techniques and algorithms
  • Statistical computer languages (Python (preferred), R SAS, etc.)


Shift:
1st shift (United States of America)

Hours Per Week:
40

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