Manager, Quantitative Analysis - Model Risk Office

Hobbsnews

New York (NY)

On-site

USD 215,200 - 245,600

Full time

14 days+

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Benefits offered by this job

Performance-based incentives
Health and financial benefits
Inclusive work environment

Job summary

Capital One seeks a Manager for Quantitative Analysis to validate models for pricing and risk management. The role involves collaborating with teams to ensure model accuracy and communicating results to various stakeholders.

Qualified candidates will possess a Master’s or PhD in a quantitative field and have a strong track record in econometric modeling, machine learning, and programming in R or Python. Capital One offers competitive salaries and comprehensive benefits.

Qualifications

  • Master's degree or PhD in a quantitative field.
  • 4+ years of experience in statistical or econometric modeling.
  • Experience with programming in R, Python, or SQL.

Responsibilities

  • Validate models used for derivative pricing and risk management.
  • Develop model approaches and document findings.
  • Communicate results to non-technical stakeholders.

Skills

Statistical or econometric modeling
Programming in R, Python, or SQL
Machine learning
Strong communication skills

Education

Master’s or PhD in a quantitative field

Tools

Python
R

Job description

Manager, Quantitative Analysis - Model Risk Office

At Capital One data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data‑driven decision‑making.

As a Quantitative Analyst at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in cloud computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Capital One is selectively recruiting for a Manager for a Model Validation team. The individual would report to the Model Risk Office and work closely with the business groups. This individual, along with their peers, would be responsible for ensuring the accuracy and robustness of the firm’s market risk models. Clients of the group include senior management, business leads, internal audit, and the regulators.

This position is responsible for validating models, specifically those used for derivative pricing and risk management, including derivative valuation, market risk, and counterparty risk models. Strong communication skills are essential to effectively engage with a diverse group of stakeholders, irrespective of their technical background.

Responsibilities
  • Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
  • Develop model approaches to assess model design and advance future capabilities
  • Understand relevant business processes and portfolios associated with model use
  • Understand technical issues in econometric, statistical, and machine learning modeling and apply these skills toward developing models and assessing model risks and opportunities
  • Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non‑specialist audiences and senior management
  • Maintain the efficiency and accuracy of our models through continuous improvement and application of best practices
  • Develop and maintain high quality and transparent documentation
  • Leverage the latest open source technologies and tools to identify areas of opportunity in our existing framework

Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation.

Successful candidates will possess
  • Demonstrated track‑record in modeling and experience utilizing model estimation tools such as Python or R
  • Ability to clearly communicate modeling results to management, model risk office, regulator and other modelers
  • Drive to continuously improve all aspects of their work in a collaborative fashion
  • Experience in machine learning
  • Strong communication skills with the ability to quickly understand existing models and new requirements/business needs
  • Experience working with Agile development methodologies
  • Strong grasp of econometric theory and methodologies
  • Desire to remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
  • Experience working with CCAR regulatory requirements
  • Experience with derivative modeling
Basic Qualifications
  • Currently has, or is in the process of obtaining one of the following with an exception that the required degree will be obtained on or before the scheduled start date:
    • A Master’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience in quantitative analytics
    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience in quantitative analytics
  • At least 4 years of experience in each of the following skills through education or experience:
    • Statistical or econometric modeling
    • Linear and logistic regression
    • Programming in R, Python, or SQL
    • Presenting statistical concepts and research results to non‑statistical audience
  • At least 4 years of experience in at least 3 of the following skills:
    • Survival analysis modeling
    • Time‑series analysis
    • Panel data (longitudinal data or cross‑sectional time‑series data) analysis
    • Cross‑sectional data analysis
    • Machine learning
    • Analysis and management of large datasets (>1M records)
Preferred Qualifications
  • 5 years of experience with Python, R or other statistical analyst software
  • 5 years of experience in statistical modeling or regression analytics or machine learning
  • At least 2 years of experience in derivative modeling (Fixed income, Commodity, FX or CDS)

Capital One will consider sponsoring a new qualified 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.

New York, NY: $215,200 - $245,600 for Manager, Quantitative Analysis

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.

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.

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