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Senior Associate, Artificial Intelligence and Machine Learning Technical Risk - Enterprise Services Risk, Cyber Risk & Analysis

Senior Associate, Artificial Intelligence and Machine Learning Technical Risk - Enterprise Services Risk, Cyber Risk & Analysis
McLean; Richmond; New York
·
On-site
·
Full-time
·
1mo ago
Required skills
Machine Learning
Project Management
- Senior Associate, Artificial Intelligence and Machine Learning Technical Risk
- Enterprise Services Risk, Cyber Risk & Analysis
The Enterprise Services Risk organization is expanding with a focus on attracting innovative, pioneering, collaborative, and highly skilled professionals. We operate at the forefront of risk management, providing support for novel and developing technologies, as well as critical business strategies. Diverse perspectives and experiences are valued as we work to redefine the financial sector.
As an AI/ML Risk Guide supporting the Enterprise AI/ML Program, you will partner and support colleagues across product, design and tech to deliver results that have a direct impact on customer experience and implement risk solutions to ensure Capital One’s continued stability and success. You should consider this role if you’re someone who enjoys wearing multiple hats, fast paced environments, and collaborating across teams and disciplines throughout the enterprise. This role operates within a dynamic environment with changing conditions and a core component of success is building relationships and influencing decision makers with grounded data. In this role you’ll successfully manage multiple concurrent deliverables while ensuring a high level of attention to details, achieve project milestones and deliverables within established deadlines, and provide clear and consistent communication to support accuracy and team alignment.
In this role, you will:
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Assist in the development and execution of the ES Risk vision and deliver on enterprise and team objectives.
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Deliver on the identification and development of risks, issues, and/or mitigation plans to ensure product and tech teams within the business implement needed changes and address areas of exposure.
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Develop and communicate risk management reporting and communications
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Collaborate effectively with colleagues, stakeholders, and leaders across multiple organizations to achieve strategic objectives
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Coordinate program-related activities and deliverables to ensure effective collaboration within the team and across stakeholder groups
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Innovate and improve our approach to risk management.
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Establish and maintain relationships with Enterprise Services process owners, process managers, and vertical risk advisors
Basic Qualifications:
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High School Diploma, GED or Equivalent Certification
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At least 2 years of experience in Risk Management, Process Management, Project Management, or a combination of these
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At least 1 year of Compliance, Legal, Regulatory or Operations experience
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At least 1 year of experience in Technology, Cybersecurity, Artificial Intelligence, or Machine Learning
Preferred Qualifications
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Bachelor's Degree or Military Experience
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Certifications such as Certified Information Systems Security Professional (CISSP), Certified Information Security Manager (CISM), Project Management Professional (PMP) Certification, or Masters Certificate of Project Management (CPM)
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2+ years of experience in Process management
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2+ years of experience in Change Management or Risk Management
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1+ years of experience as a Risk Guide
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1+ years of experience in Risk Management related to Machine Learning
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Ability to drive results and communicate with all levels
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Knowledge of appropriate controls to secure cloud-based services (SaaS) products
At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Mc Lean, VA: $111,200 - $126,900 for Sr. Assoc, Cyber Risk & Analysis
Richmond, VA: $101,100 - $115,400 for Sr. Assoc, Cyber Risk & Analysis
New York, NY: $121,300 - $138,400 for Sr. Assoc, Cyber Risk & Analysis
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at Recruiting Accommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
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About Capital One

Capital One
PublicA financial services company that provides banking, credit card, auto loan, savings, and commercial banking services.
10,001+
Employees
Mclean
Headquarters
$30B
Valuation
Reviews
3.9
10 reviews
Work-life balance
3.2
Compensation
4.0
Culture
3.8
Career
3.5
Management
3.7
72%
Recommend to a friend
Pros
Flexible work arrangements and hours
Good benefits and competitive compensation
Supportive team dynamics and collaboration
Cons
High workload and long hours
High pressure and stress during peak times
Limited career advancement opportunities
Salary Ranges
88 data points
L2
L3
L4
L5
L6
M3
M4
M5
M6
Mid/L4
Senior/L5
L2 · Data Scientist L2
0 reports
$113,205
total per year
Base
$45,282
Stock
$56,603
Bonus
$11,321
$79,244
$147,167
Interview experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
40%
Experience
Positive 40%
Neutral 60%
Negative 0%
Interview process
1
Application Review
2
Online Assessment (CodeSignal)
3
Recruiter Phone Screen
4
Technical Interview
5
Behavioral Interview
6
Power Day/Super Day
7
Final Round/Offer
Common questions
Coding/Algorithm
Data Analysis
Behavioral/STAR
Technical Knowledge
System Design
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