Senior Manager, Quantitative Analysis - Model Risk Job at Capital One (McLean)

Senior Manager, Quantitative Analysis - Model Risk Office

Senior Manager, Quantitative Analysis - Model Risk Office At Capital One data i...

Location

United States , McLean

Salary:

229900.00 - 262400.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

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 5 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 2 years of experience in quantitative analytics
At least 5 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 5 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

Job Responsibility

Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
Develop alternative 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

What we offer

performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits

Fulltime

Senior Manager, Data Science - Model Risk Office

Senior Manager, Data Science - Model Risk Office Data is at the center of every...

Location

United States , McLean, Virginia; Richmond, Virginia; Riverwoods, Illinois; New York, New York

Salary:

229900.00 - 286200.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics
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 5 years of experience performing data analytics
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases

Job Responsibility

Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Flex your interpersonal skills to translate the complexity of your work into tangible business goals

What we offer

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits

Fulltime

Senior Model Risk Management Analyst

Lead is seeking a dynamic, self-motivated senior analyst to join our Model Risk ...

Location

United States , Kansas City; New York; San Francisco; Sunnyvale

Salary:

125000.00 - 175000.00 USD / Year

Lead Bank

Expiration Date

Until further notice

Requirements

Hold a Bachelor’s Degree or higher in a quantitative discipline such as math, physics, econometrics, statistics, or financial engineering
Have 5 or more years of working experience in quantitative / statistical model development, model validation and/or model risk management
Familiarity with traditional statistical models (e.g. linear / logistic regressions) as well as more advanced machine learning models (e.g. gradient boosting models)
Possess a strong quantitatively oriented knowledge of financial products and industry best practices and regulatory requirements for model risk management
Strong verbal and written communication skills
Have a collaborative mind-set with strong interpersonal skills
Excel at explaining highly technical, complex concepts so that internal and external partners with diverse backgrounds can understand
Highly adaptive, flexible and able to execute to rapidly changing conditions and priorities

Job Responsibility

Track ongoing oversight of model usage of Lead Bank’s partners throughout the model life cycle
Track KRIs related to model performance and efficacy
Review model validation, development, and ongoing monitoring documentation for a range of models from scorecards, regressions, and other machine learning algorithms across the various products offered by Lead’s partners
Assist in the maintenance of Lead’s Model Inventory
Assist with due diligence on fintech partner model risk management process as part of partner onboarding
Engage with stakeholders: Work closely with partner program managers, risk, finance, legal/compliance, customers/partners, and other related function group personnel to identify, assess, monitor, and manage model risk proactively
Design and produce model risk metrics and reporting for internal Board Committees and other stakeholders
Perform other duties as assigned

What we offer

Competitive compensation based on experience, geographic location, and role
Medical, Dental, Vision, Life, 401k Matching, and other wellness benefits, including FSA, HSA and HRA
Paid parental leave
Flexible vacation policy, including PTO and paid holidays
A fun and challenging team environment in a dynamic industry with ample opportunities for career growth

Fulltime

Risk Model Senior Analyst

Risk Model Senior Analyst role in Citi's Risk Management organization, part of t...

Location

Philippines , Taguig

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

At least 4-5 years of relevant experience in creating, validating and reviewing models
Undergraduate degree in a quantitative or technical discipline such as Computer Science, Engineering, Physics, Statistics, Quantitative Finance
Master's degree or higher in quantitative disciplines a plus
Knowledge of or interest in finance, markets, risk management
Ability to apply sophisticated mathematical/analytical techniques to solve real-world problems
Proficient in Python, Java, or Scala in a Unix/Linux environment
Candidate must be proficient in PYTHON

Job Responsibility

Prepare detailed quantitative modeling and analysis for risk managers and senior management
Synthesize and communicate complex risk models and results
Conduct statistical analysis, quantitative modeling, and model risk controls
Work with risk managers, businesses, and tech to design and build models for risk capture and stress testing

What we offer

Access to telehealth options, health advocates, confidential counseling
Expanded Paid Parental Leave Policy
Programs to manage financial well-being and help plan for the future
Access to learning and development resources
Generous paid time off packages
Resources and tools to volunteer in communities

Fulltime

Senior Manager- Data Analysis

Senior Manager- Data Analysis. At Capital One, data is at the center of everythi...

Location

United States , Plano

Salary:

182500.00 - 208300.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Currently has, or is in the process of obtaining a Bachelor’s Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 7 years of experience performing data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus at least 5 years of experience performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date
At least 5 years of experience performing professional data analysis work
At least 5 years of experience leading and developing with open source data technologies
At least 2 years of experience managing people

Job Responsibility

Refining a new Enterprise-wide analytical tools validation framework
Planning and executing validation projects
Assessing the quality and risk of analytical tool methodologies across Capital One, and the nature of tools usage within those processes
Understanding technical issues in analytical tools and assessing tools risks and opportunities
Independently researching, identifying, and prototyping industry best practices for emerging analytical tools
Communicating results clearly and concisely both verbally and through written communications via validation reports and presentations
Leveraging education, colleagues and training opportunities to develop solutions to business problems
Coaching and mentoring junior staff

What we offer

performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits

Fulltime

Senior Project Risk Manager

At Stegra, we’re not just building a plant, we’re proving that sustainable indus...

Location

Sweden , Stockholm

Salary:

Not provided

Stegra

Expiration Date

Until further notice

Requirements

Degree in Project Management, Risk Management, Engineering, or related field, with professional certification (e.g. PMI-RMP, PMP, MoR, Prince2, AACE DRMP)
15+ years of experience in project or risk management within capital-intensive industries (energy, mining, infrastructure, etc.)
Proven facilitation skills in leading risk workshops and strategic assessments with cross-functional teams
Proficient in quantitative risk analysis using Monte Carlo simulations and tools like Safran Risk, @RISK, or Primavera Risk Analysis
Understanding of project risk management grounded in international standards such as ISO 31000, ISO 31010, and IEC 62198, as well as frameworks including PRAM, PMI PMBOK, and the AACEI TCM 7.1 Framework and recommended practices
Skilled in integrating risk insights across cost estimating, scheduling, procurement, and project controls
Excellent communication skills in English (Swedish is a plus), with strong interpersonal abilities and coaching experience in risk management practices

Job Responsibility

Develop and implement risk plans for capital projects across all lifecycle phases (FEL1 to execution)
Facilitate structured assessments, project risk workshops, technical and non-technical
Update of risk registers, support risk and action owners, and verify mitigation activities
Plan and facilitate Quantitative Risk Analysis (QRA) workshops and model capital risk profiles
Perform integrated cost and schedule Quantitative Risk Analysis (QRA) using industry tools such as Safran Risk and @RISK
Oversee maintain, monitor, and analyze project risk registers to ensure proactive mitigation and alignment with project objectives
Support risk-based decision-making at both the project and program level through clear communication methods
Provide coaching and training to project teams on risk principles and methods, and collaborate closely with project functions such as Planning, Cost, HSE, and Engineering to embed risk management into project systems and culture
Assess internal and external project environments to tailor and implement project-specific risk management plans
Configure project risk structures (registers, matrices, breakdowns), and lead facilitation of workshops to develop project risk profiles

What we offer

Fair, competitive compensation aligned with collective agreements
Up to 30 days of paid vacation
Occupational pension
Parental benefits
Insurance
Support with relocation or immigration
Subsidized gym memberships
Bike leases

Fulltime

Senior Machine Learning Engineer, Model Risk Management

Block lends, moves money, and screens for financial crime at enormous scale, and...

Location

United States , New York

Salary:

194500.00 - 343100.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

A quantitative degree or equivalent experience, and senior-IC depth building or validating models in a high-stakes domain such as credit, fraud, or financial crime
Command of effective-challenge methodology: reproduction, conceptual-soundness review, benchmarking, stress testing, and outcomes analysis, with an eye for how a model holds up after launch and where its assumptions break
Deep applied ML and statistics across model families, from regression and tree ensembles to deep learning, with sound judgment about evaluation, calibration, and generalization
Experimentation and statistical rigor: holdout and experiment design, reasoning about uncertainty, and evaluating a model beyond aggregate accuracy
Solid software and data engineering: production-quality Python, SQL on large datasets, and reproducible, tested code
Fluency with modern AI: building with LLMs and agentic tools, and the judgment to know when their output can be trusted
Familiarity with model risk management frameworks and fair-lending standards, with the specifics learnable on the job
The communication to explain and defend your conclusions to model owners and senior stakeholders, and the independence to operate under ambiguity

Job Responsibility

Independently challenge model owners across lending, fraud, and AML: reproduce their results, set and defend the acceptance thresholds, and own the call on whether a model is sound
Hunt the silent errors that make metrics lie, and prove them out before they reach production
Choose evaluation that holds up under real conditions: rare events, shifting populations, and drift that only shows up after launch
Work hands-on in codebases you did not write, learning the data, configs, and conventions, and ship production code in the tooling you build to validate them
Build the agentic validation tooling the team depends on, orchestrating agents that run in parallel
Reason about ML systems end to end — how features, training, serving, monitoring, and scale fit together — to evaluate and challenge an owner's design
Tie explainability and fair-lending findings on consumer credit models back to the model and product decisions that follow
Help define how Block validates the systems at the frontier of production AI, setting standards where none exist yet

What we offer

Remote work
Medical insurance
Flexible time off
Retirement savings plans
Modern family planning

Fulltime

Assistant Vice President (AVP), Non-Financial Risk – Data & Model Risk Specialist

The Assistant Vice President (AVP), Non-Financial Risk - Data & Model Risk Speci...

Location

United Kingdom , Belfast

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Minimum of 5-8 years of experience in operational risk management, compliance, audit, or other control-related functions in the financial services industry
Ability to identify, measure, and manage key risks and controls
Strong knowledge in the development and execution for controls
Proven experience in control related functions in the financial industry
Proven experience in implementing sustainable solutions and improving processes
Understanding of compliance laws, rules, regulations, and best practices
Understanding of Citi’s Policies, Standards, and Procedures
Strong analytical skills to evaluate complex risk and control activities and processes
Strong verbal and written communication skills, with a demonstrated ability to engage at the senior management level
Strong problem-solving and decision-making skills

Job Responsibility

Conduct comprehensive non-financial risk assessments for new and existing data initiatives, data flows, and analytical models, focusing on data governance, data quality, data privacy, model development, model validation, regulatory compliance, and reputational risk
Support the implementation and continuous enhancement of Citi’s Data and Model Risk Management (DMRM) framework, policies, and procedures within the Client Organization
Establish and execute ongoing monitoring activities for critical data assets and models, including data quality metrics, model performance reviews, validation effectiveness evaluations, and incident management
Identify and escalate emerging data and model risks. Collaborate with business owners, technology teams, and model developers to develop and implement effective risk mitigation plans and corrective actions
Partner closely with business units, Technology, Quantitative Risk, Compliance, and other risk functions to ensure a consistent and integrated approach to data and model risk management
Contribute to developing and delivering training and awareness programs on data and model risk management best practices for business stakeholders
Provide oversight and direction for model lifecycle governance, including model onboarding, changes, validations, limitations, inactive models, and annual lifecycle reviews
Influence and partner with senior stakeholders across functions and regions to embed controls, strengthen governance, and drive consistent execution
Lead analysis of control environments and processes, identifying strategic opportunities to enhance control effectiveness, operational efficiency, and overall governance maturity

Fulltime

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Senior Manager, Quantitative Analysis - Model Risk

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