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Consultant Quantitative Finance Financial Engineering (m W D) In Düsseldorf

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Quant Senior Quant Analyst – Market Risk Model Validation (FRTB)

We are seeking a highly analytical and detail-oriented individual to join our Model Validation team at Crisil. As a key member of the team, you will be responsible for the independent validation of market risk models under the Fundamental Review of the Trading Book (FRTB) framework. This includes both the Internal Model Approach (IMA) and the Standardized Approach (SA). The role requires a deep understanding of quantitative finance, regulatory requirements, and strong technical skills to ensure our models are conceptually sound, robust, and fit for purpose.

Core Responsibilities:

Independent Model Validation (IMA):

Validate the Expected Shortfall (ES) models, including calibration, risk factor mapping, and stress scenarios.
Assess the P&L Attribution (PLA) test framework and its implementation to ensure desk-level model eligibility.
Review the identification, treatment, and capitalization of Non-Modellable Risk Factors (NMRF).
Perform rigorous back testing on the internal models at both desk and aggregate levels as per regulatory standards.

Independent Model Validation (SA):

Validate the implementation of the Sensitivities-Based Approach (SBA), including the calculation of delta, vega, and curvature risk sensitivities.
Review the aggregation formulas and correlation scenarios as prescribed by the regulation.
Assess the calculation of the Default Risk Charge (DRC-SA) and the Residual Risk Add-on (RRAO).

Quantitative Analysis & Testing:

Conduct challenger model development for benchmarking and performance assessment.
Perform extensive sensitivity analysis on model assumptions, parameters, and inputs.
Design and execute stress tests to probe model vulnerabilities under extreme but plausible scenarios.

Documentation & Governance:

Author comprehensive and high-quality model validation reports, clearly outlining findings, limitations, and required actions for remediation.
Present validation results to senior management, model governance committees, and internal/external auditors.
Maintain the model inventory and track the lifecycle and remediation of validation findings.

Essential Qualifications & Experience:

Education: Master’s or Ph.D. in a quantitative discipline (e.g., Financial Engineering, Mathematics, Physics, Statistics, Economics).
Experience: [2–6] years of experience in a quantitative risk role (model validation or development) within a financial institution or top-tier consulting firm. Direct experience with market risk models is mandatory.
FRTB Knowledge: In-depth, demonstrable knowledge of the FRTB framework, including both the Internal Model Approach and the Standardized Approach, based on the BCBS standards.

Technical & Professional Skills:

Programming: Strong proficiency in Python (preferred) for data analysis and model prototyping. Experience with libraries like Pandas, NumPy, and Scikit-learn is essential.
Database: Competency with SQL for data extraction and manipulation.
Quantitative: Solid understanding of financial mathematics, derivatives pricing, and statistical modeling (e.g., time series analysis, Monte Carlo methods).
Communication: Exceptional written and verbal communication skills, with the ability to explain complex quantitative concepts to diverse audiences, including senior management and regulators.
Certifications: FRM or CQF designation is highly desirable.

Investment Professional

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ALM Risk And Technology Consultant

About this position:

The Office of Risk Management (RMG) is seeking a dynamic and innovative consultant in ALM Risk and Technology to support the implementation of a system solution for Asset and Liability Management.

What you’ll do:

Integrate into the project team for the end-to-end implementation of the ALM solution, including requirements definition, configuration, implementation, and testing.

Act as a subject matter expert in Asset and Liability Management (ALM).

Learn the unique operational model of the institution and prepare requirements documentation that accurately reflects the Balance Sheet features (e.g., loan pricing mechanism, Equity Duration, Liquidity Floor) to support the discovery phase with the system vendor.

Act as a liaison between internal stakeholders (Risk, Finance, IT) and the solution vendor to ensure that requirements are clearly understood and effectively delivered.

Contribute to the preparation and validation of functional documentation related to ALM methodologies, such as interest rate risk (IRRBB), liquidity risk, and financial projections.

Review and validate system outputs, reports, and dashboards generated by the ALM solution to ensure alignment with defined requirements and stakeholder expectations.

Coordinate with the Project Management Office (PMO) to monitor project milestones, track deliverables, identify risks, and propose mitigation strategies as needed.

Assist in the preparation of project status updates, stakeholder communications, and implementation reports, as required.

Assist with the production of the Quarterly Risk Management Report for the Board of Directors by preparing parts of ALM/Liquidity sections, charts, tables, or annexes.

Collaborate in financial projection models to forecast NII, retained earnings and equity position, applying interest rate scenarios and stress tests.

Generate valuation and risk analytics to assess the impact of interest rates on the Banks Net Interest Income (NII), economic value of equity (EVE), and duration of equity.

Monitor and prepare reports on the balance sheet net fixed exposure, repricing gap, basis risk and liquidity metrics.

Run data reconciliation processes for financial projections.

What you’ll need:

Education: Masters degree in Finance, Business Administration, Economics, Statistics, Mathematics, or other related quantitative discipline.

At least 5 years of experience in finance, asset-liability management, risk management and/or fixed income with exposure to balance sheet planning and risk analytics.

Experience designing and implementing financial systems at banks. Experience with Asset & Liability Solutions (QRM, SAS-Kamakura, Algorithmics, Empyrean, FIS) highly preferred.

Knowledge of Interest Rate Risk Management of the Balance Sheet (IRRBB).

Outstanding analytical and problem-solving skills. Strong communication skills, including the ability to draft well-written, coherent analyses and documents for senior management.

CFA, FRM or CQF certification is desirable.

Head Of Commodities RV Portfolio Manager

Our client is building out a new Relative Value Commodities business. This is a completely blank canvas with no one in the business currently running Commodity strategies. The fund is open to all different types of Commodities Portfolio Managers from Discretionary, Quantamental, and fully automated, Cross-Commodity, Cross-Energy, Metals, etc.

The major requirement here is that you have experience building a business previously within your own vertical. You must have an idea of market connectivity, data vendor sources, costs, runway timelines etc. The fund will absorb a large portion of the costs to get you up and running, and there is flexibility around IP ownership and DD limits. The centralized quantitative resources will be at hand to assist with the infrastructure buildout.

Must have:-

Current live positive track record with a Sharpe of 1.5+.
$20Mn+ PnL
Extensive experience in the Commodities arena.
Built a Commodities business before.
Expertise in either Cross-Commodities, Cross Energy, or Metals strategies.
If quant then a CQF qualification would be a bonus.

Senior Quant Researcher Systematic Macro RV

A leading $10+ billion hedge fund has a strong established Macro desk and right now is seeking to expand it and hire multiple senior quant researchers, who will be sub-portfolio managers to lead the direction of statistical arbitrage RV strategy in commodities (metals, softs and power). You get your own carve out from the central book, and your compensation will be PnL driven, based on the profit your signals generate. The opportunity here is that you will be a part of the centralised Macro desk and collaborate with other quant researchers to develop systematic Stat Arb macro strategies and get the PnL cut, but at the same time you don’t need to be a standalone portfolio manager and manage a team.

Exceptional in Python or C++ coding skills.
Track record of generating positive alpha at least 3+ years
Systematic Macro strategies in Commodities (softs, metals, energy/power)
Global markets (US, Europe, Asia)
CQF preferred

Commodities Portfolio Manager

A close hedge fund client of ours is building out a new Commodities pod business. They are in their infancy of the build-out and are open to all different types of Commodities Portfolio Managers from Discretionary, Quantamental, and fully automated, Cross-Commodity, Cross-Energy, Metals, etc.

Must have:-

Current live positive track record with a Sharpe of 1.5+.
$15Mn+ PnL
Extensive experience in the Commodities arena.
Built a Commodities business before.
Expertise in either Cross-Commodities, Cross Energy, or Metals strategies.
If quant then a CQF qualification would be a bonus.

Risk Consulting (FSRM) – Senior Associate

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System Modeler

Roles & Responsibilities

Build and maintain financial models (e.g., cash flow forecasts, NPV/IRR, capital planning) to translate operational metrics into financial insights.
Conduct scenario planning, stress tests, and sensitivity analysis to evaluate strategic business decisions.
Validate model assumptions through back-testing and ensure predictive stability.
Collaborate with analytics, finance, and operations teams to align data, inputs, and result interpretation.
Maintain model auditability, versioning, and documentation in a certified model catalog.
Enhance models with advanced techniques (stochastic drivers, real options valuation, tornado analyses) to support strategic and operational decisions.

Requisites

Bachelor’s degree in Statistics, Finance/Economics, Computer Science, or related field.
Experience in financial modeling, scenario planning, and sensitivity analysis.
Strong Python and SQL skills for analytics and automation.
Ability to communicate insights and trade-offs to business stakeholders.
Preferred: Advanced degree, experience in energy/asset-intensive industries, optimization/system dynamics knowledge, cloud platforms, or professional credentials (CFA, CQF).

VP, Portfolio and Quantitative Analytics – Lazard Wealth

Lazard is one of the world’s preeminent financial advisory and asset management firms. Our people and culture make the difference. While global in presence and reach, ours is a close, collaborative community of just over 3,000 professionals. Lazard is a place of continuous knowledge sharing, skill development and relationship building, where professionals grow and succeed together. Our entrepreneurial culture, flat structure and embrace of individual differences, allow creative ideas, original concepts, and unique perspectives to drive our business forward — and for careers to take flight.

Lazard Wealth, LAM’s wealth management business, collaborates with our clients to help solve and simplify the complexities of wealth, while delivering sophisticated investment solutions and advice. We combine years of history and experience to help preserve and grow our clients’ wealth across generations. The principal areas of focus with clients are strategic advice and planning, investment management and direct private investments. Working in partnership with families, we customize an investment process that meets their specific needs.

We are seeking a Vice President of Portfolio and Quantitative Analytics to play a critical role in supporting and overseeing quantitative and risk management functions within our firm. You will be responsible for developing and implementing effective risk management strategies, programming models, reports, and procedures across client portfolios, market research, and technology solutions.

We’ll trust you to:

Develop and maintain models and tools to identify and monitor portfolio risk factors, stress test portfolios, and ensure compliance with risk management guidelines.
Proactively monitor market conditions and perform scenario analysis to assess potential impacts on portfolio risk exposures and recommend necessary adjustments.
Participate in portfolio and investment decisions and contribute to the development of investment strategies, asset allocation models, privates modeling and risk management frameworks- incorporating quantitative research insights.
Utilize advanced statistical techniques and quantitative models to assess portfolio and investment risk, estimate potential returns, and optimize portfolio construction in order to deliver performance attribution analysis, factor-based exposures, and portfolio optimization.
Stay updated on the latest industry trends and research advancements in risk management, quantitative analysis, and portfolio construction methodologies.
Collaborate with other groups within the Firm to offer quantitative support and industry specific input.
Support the Investment Team with quantitative research and analysis of investment opportunities across various asset classes, including equities, fixed income, and alternative investments (privates and real assets) with a strong focus on risk management and portfolio construction.
Evaluate and implement risk management techniques, such as hedging strategies, derivatives, and asset allocation adjustments, to mitigate portfolio risks and enhance risk-adjusted returns.

You’ll need to have:

Proven experience in risk management, quantitative research, or a related role within the wealth management industry.
Proven experience in MATLAB for programming and software development.
Strong understanding of risk management principles, quantitative modeling techniques, and statistical analysis.
Highly proficiency in programming languages such as R or MATLAB for quantitative research, data analysis, model implementation and creation of interactive dashboards.
Strong ability to access, manipulate, and clean large data sets from various databases and sources.
Ability to prioritize and manage multiple tasks and projects effectively.
Experience with risk modeling software, quantitative analytics platforms, and market data providers (e.g. Bloomberg).
Familiarity with risk measurement methodologies (e.g., VaR, stress testing, factor analysis) and risk management frameworks (e.g., risk budgeting, risk-adjusted performance metrics).
Knowledge of financial derivatives, options pricing models, and portfolio optimization techniques.
Excellent problem-solving and critical-thinking skills, with the ability to analyze complex data sets and draw meaningful insights.
Strong communication and presentation skills, with the ability to explain quantitative concepts to non-technical stakeholders.
Bachelor’s degree in finance, economics, mathematics, statistics, or a related field. Advanced degree (e.g., MBA, MSc) with a focus on quantitative finance or risk management is preferred.
5-10 years’ experience in a risk management, analytical, or quantitative role, particularly within the asset allocator and wealth management space.
Demonstrates a strong interest in working on a wide range of problems related to diverse asset classes and investment strategies. Understanding or interest in learning about alternative asset classes.
Professional certifications such as FRM, CQF, or CFA are desirable.