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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.

Risk Analyst

What you will do

Focusing on short-term power market specifics – PnL / Earnings-at-Risk (EaR) / VAR / stress analytics – run real‑time risk
End of day PnL reports, risk attribution, and validation of curves and market result
Algo & model validation – participate in development process to identify potential risk and compliance issues
Limit framework & monitoring – Follow up exposure compared to set limits and report deviations
Post‑trade performance analytics – decompose PnL into forecast error, execution slippage and asset availability; feed insights back to the trading and data‑science / Machine learning teams.
Provide guidance on market rules and bidding methodologies to ensure Remit compliant trading strategies
Work with stakeholders to continuously identify and reduce operational risk
Reporting: Verify trade reporting, Check trade logs, support regulatory audits
Promote a culture of ethical behavior, transparency, and accountability across the organization
Trade surveillance

Job requirements

Experience and education

3+ years’ hands-on experience in a front line risk position within the energy trading sectors.
Degree in a quantitative field such as Engineering, Data or Computer Science, Mathematics, Physics or Finance Engineering; professional risk certifications (e.g. FRM, CQF) are an advantage.
Experience with trade surveillance tools and compliance monitoring systems.
Strong understanding of BESS operations and market participation structures is a plus.
Fluent written & spoken English; additional European languages a plus.

What you will need

Hands‑on, self-starter DNA – you’re comfortable rolling up sleeves, shipping quick wins and iterating fast.
Deep knowledge of European short‑term power markets – DA, ID continuous, FCR, aFRR/mFRR, BRP imbalance settlement is a must have
Experience in an asset-backed trading environment , particularly with focus on BESS / Flex asset optimization is a strong plus
Experience in algorithmic trading risk and compliance is a strong plus

Senior Quantitative Risk Analyst

We are always looking for talented and motivated colleagues to join our team and together, contribute to the creation of a sustainable future, based on inclusion, empathy, respect and equal opportunities.

The main goal is identifying, analyzing and mitigating potential risks that could impact the company.

Together with us, you have the chance to grow everyday, contributing to energy transition, being responsible to:

Design, implement, and validate quantitative risk models for financial, operational, and market risks.
Apply advanced statistical techniques (hypothesis testing, regression analysis, confidence intervals, etc.) to assess risk drivers.
Develop forecasting models for risk trends and exposures.
Conduct Value at Risk (VaR), Profit at Risk (PaR), stress-testing analysis, Monte Carlo simulations and stochastic modeling techniques to quantify potential outcomes under uncertainty.
Document model assumptions, limitations, and validation results in line with best practice and governance requirements.
Provide training and guidance to junior analysts in the use of advanced quantitative methods.
Collaborate with other departments (Trading, Treasury, Operations etc) to integrate quantitative risk insights into business decision-making.
Prepare clear, concise, and actionable reports for management.

What you’ll need to succeed:

At least 5 years of proven experience in statistics / quantitative analysis
Experience in energy sector risk management or commodity markets is a plus.
Bachelor’s degree (mandatory) or Master’s degree (preferred) in Statistics, Mathematics, Quantitative Finance, Finance, Economics, Engineering, or related field.
Certifications like Certificate in Quantitative Finance (CQF), Financial Risk Manager (FRM), Certified Risk Manager (CRM), Professional Risk Manager (PRM) or equivalent are a strong plus.
Technical excellence in quantitative / statistical / stochastical modeling.
Competence in at least one statistical software / programming language: Python, R, MATLAB, or SAS is a strong plus.
Knowledge of COSO ERM and/or ISO 31000 risk management frameworks is a plus.
Excellent communication and presentation skills.
Strong analytical and problem-solving skills.
Curiosity, innovation, and continuous learning mindset.
Strong ethical standards and commitment to risk governance.

FS-RISK CONSULTING-FSRM – QTB-SENIOR

EY’s Financial Services Office (FSO) is a unique, industry-focused business unit that provides a broad range of integrated services that leverage deep industry experience with strong functional capability and product knowledge. FSO practice provides integrated advisory services to financial institutions and other capital markets participants, including commercial banks, investment banks, broker-dealers, asset managers (traditional and alternative), insurance and energy trading companies, and the Corporate Treasury functions of leading Fortune 500 Companies. The service offerings provided by the FSO Advisory include: market, credit and operational risk management, regulatory advisory, quantitative advisory, structured finance transaction, actuarial advisory, technology enablement, risk and security, program advisory, and process & controls.

Within EY’s FSO Advisory Practice, the Financial Services Risk Management (FSRM) group provides solutions that can help FSO clients to identify, measure, manage and monitor the market (trading book), credit (banking book), operational, and regulatory risks associated with their trading, asset-liability management, capital management and other capital markets activities.

Within FSRM, the Quantitative Trading Book (QTB) team assists clients to design and implement strategic and functional changes across risk management, treasury, front office, middle office, and back-office activities with a focus on risk and valuation processes, regulatory compliance, analytics, strategy, and organizational structure. Practical implementation knowledge of risk and capital management is a key competency of QTB, focused on regulatory capital, market and counterparty credit risk management and broker-dealer capital requirements. Clients include large domestic and global financial institutions, broker-dealers, foreign banking organizations, asset management firms and insurance companies with significant capital markets activities.

Your key responsibilities

Demonstrate deep technical capabilities and industry knowledge of financial products
Lead components of large-scale client engagements and/or smaller client engagements while consistently delivering quality client services
Understand market trends and demands in the financial services sector and issues faced by clients by staying abreast of current business and industry trends relevant to the client’s business
Monitor progress, manage risk, and effectively communicate with key stakeholders regarding status, issues and key priorities to achieve expected outcomes
Play an active role in mentoring junior consultants within the organization

To qualify for the role, you should have:

Undergraduate (4-year degree) or Masters (Computational Finance, Mathematics, Engineering, Statistics, or Physics preferred) or Ph.D. in quantitative topics.
Working knowledge or academic experience of statistical and numerical techniques (E.g., Monte-Carlo methods, Finite difference methods)
Knowledge of mathematical concepts and domain knowledge related to pricing derivatives for any of the asset classes such as fixed income, equities, credit, interest rates, FX, and commodities
Strong risk management/model development/validation knowledge in market risk (VaR, Stressed VaR, Expected Shortfall, etc.) and/or counterparty credit risk (CVA, PFE, etc.).
Good hands-on experience in model development/validation/monitoring/audit procedures (including Stress testing, Back-testing, Benchmarking, etc.).
Knowledge of mathematical concepts like Stochastic Calculus, Differential and Integral calculus (ODE/PDE/SDE), Numerical Methods, Linear algebra, Measure Theory. Related to pricing derivatives for any of the asset classes such as fixed income, equities, credit, interest rates, FX, and commodities
Development/Validation/Annual Review of Equity pricing models, Interest Rate Models (HW1F, HW2F, HJM, LMM), Stochastic Volatility (SABR, Heston) model, Local Volatility model (Dupire), frameworks for Volatility stripping and calibration, Bootstrapping of IR curves (Single curve, Multi curve framework), Asset Liability Management (NII, MVPE) and Prepayment Models.
Knowledge of Estimating Idiosyncratic volatility (specific risk) and estimating Beta, Handling missing data in time series, Validating proxy time series.
Strong coding skills in Advanced Python or Java, C++ with combination of Statistical packages in R. Basic knowledge of SQL is expected.
Excellent communication and strong problem-solving skills.

Good-to-have:

Certifications such as FRM, CQF, CFA, PRM
Regulatory knowledge/experience in areas such as Basel, CCAR, and FRTB.
Pricing/Risk management system knowledge/experience – Calypso, SunGard Adaptiv, Murex, Numerix, Bloomberg, RiskMetrics, Spectrum, EQF, etc.
Willingness to travel to meet client needs

System Modeler

Please see job role.

Working Student / Intern – Energy Trading

We are shaping the future of energy through intelligent charging and energy solutions for electric mobility. As part of the Volkswagen Group, we are building one of the first fully integrated charging and energy platforms for drivers and fleet managers of electric vehicles. Our mission is to make energy usage simple, smart, and efficient — and to actively contribute to the energy transition.

To support our growing power trading activities, we are looking for a Working Student / Intern in Energy Trading who is eager to gain hands-on experience in energy markets, quantitative analysis, and trading operations. You will work closely with experienced traders and analysts and gain deep insights into how data, models, and market dynamics come together in a real trading environment.

If you are curious about energy markets, enjoy working with data and code, and want to help shape the future of electricity trading, we’d love to hear from you.

Possible Tasks within this Role

Work closely with the power trading team and contribute to ongoing initiatives and projects.
⁠Support daily operational processes, gaining first-hand insight into market dynamics, data flows, and decision-making in a trading environment.
⁠Assist with the development, testing, and maintenance of analytical tools and quantitative models used by the team.
⁠Perform market research and data-driven analyses to support trading strategies, risk assessment, and operational improvements.
⁠Provide general operational and analytical support to the team as needed, ensuring accuracy and reliability of data and outputs.
⁠Continuously learn about power markets, products, and trading workflows, and proactively suggest improvements where possible.

Qualification requirements

Currently enrolled in a Bachelor’s or Master’s program in Mathematics, Computer Science, Engineering, Statistics, Economics, or a related quantitative field. CQF candidates or alumni highly welcome.
⁠Solid programming skills in Python and SQL; experience with additional languages or tools (e.g. Git, DevOps, CI/CD, etc.) is a plus.
⁠Strong analytical mindset with the ability to structure problems and derive insights from data.
⁠High attention to detail and confidence working with large, complex datasets.
⁠Good communication skills and the ability to collaborate effectively in a team-oriented environment.
⁠Experience with machine learning and time-series data analysis is highly desirable.
⁠Prior exposure to energy markets, trading, or quantitative finance (e.g. through coursework, internships, or projects) is a strong advantage.

Quantitative Analyst – Derivatives Pricing and Market

Our client is looking for a Quantitative Analyst to join the Market Risk and Derivatives Pricing team within their London office with hybrid working. You would be leading a series of regulatory and risk modelling projects including Derivative Pricing, Market Risk and CVA. To be successful in the role you will have a strong quantitative academic and technical background, a creative approach to work and effective communication skills.

You will use your quantitative modelling skills on a range of projects:

Model validation and testing of derivative pricing models covering equity, rates, FX, commodities asset classes; working with Front Office quants to create testing plan
Model build and validation of VAR, stressed VAR and IRC
FRTB and IBOR modelling

Qualifications and Experience Required:

Strong quantitative academic background (such as Computational Finance, Mathematics, Engineering, Statistics, or Physics), a PhD or Masters preferred
Professional Qualification e.g. CQF / CFA / FRM / PRM is advantageous
Modelling background, including experience in model development and model validation of derivative products pricing, market risk and CVA models
Significant experience in the application and justification of statistical and numerical techniques and principles of the theory of probability
Strong experience in any of the following software development environments: Python/Java /C++ / SQL/R/.NET
Good understanding of Derivative Pricing, Market and CVA methodologies used for the trading, risk management and ideally calculation of regulatory capital requirements
Experience in FRTB or IBOR transition would be preferred
Confident and credible communicator with good technical knowledge and commercial understanding

Manager – Market Risk (Quant)

You will use your quantitative modelling skills on a range of projects;

Model validation and testing of derivative pricing models covering equity, rates, FX, commodities asset classes; working with Front Office quants to create testing plan
Model build and validation of VAR, stressed VAR and IRC
FRTB and IBOR modelling

Qualifications and Experience Required:

Strong quantitative academic background (such as Computational Finance, Mathematics, Engineering, Statistics, or Physics), a PhD or Masters preferred
Professional Qualification e.g. CQF / CFA/ FRM / PRM is advantageous
Modelling background, including experience in model development and model validation of derivative products pricing, market risk and CVA models
Significant experience in the application and justification of statistical and numerical techniques and principles of the theory of probability
Strong experience in any of the following software development environments: Python/Java /C++ / SQL/R/.NET
Good understanding of Derivative Pricing, Market and CVA methodologies used for the trading, risk management and ideally calculation of regulatory capital requirements
Experience in FRTB or IBOR transition would be preferred
Confident and credible communicator with good technical knowledge and commercial understanding

Credit Risk – Senior Associate – Bangalore

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Skills

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

Credit Risk Analytics Professional Job Specification: Candidate would be responsible for developing, validating, auditing and maintaining credit risk models. Candidates would be expected to support financial institutions on meeting jurisdictional regulatory requirements and their broader risk management initiatives.

Experience level 4-7 years of experience;

Location: Bangalore

Core Skill Requirements

Candidate must have relevant experience in in statistical / mathematical modeling, quantitative research, credit risk management, or related field at a reputed bank, investment or broker services, asset management firm, Insurance provider or a consulting firm. Wider skill requirements include:

Experience in Credit Risk Modeling PD/LGD/EAD – TTC, PIT, Stressed and unstressed portfolio
Experience in Model Development, Model Validation, Model Audit (implementation and execution experience will not be considered directly relevant)
Knowledge of one or more of global regulatory norms – CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR-11/7, E-23 around data sufficiency, modeling methods, industry standards etc.
Well versed with one or more statistical techniques used in credit risk modeling – Logistic Regression, Time series, OLS, Probit models, Survival techniques, Tobit, Fractional Logistic, Beta model, State Transition Matrix, Single Factor Merton model etc
Experience in Machine learning algorithms like Random Forest, SVM, Neural Network etc. and Artificial Learning use cases such as Natural Language Processing, Robotics etc. will be a plus
Proficiency in one or more analytical tools such as SAS, R, Python, Matlab, Scala, VBA etc. Experience in Data Science and cloud based analytics platform will be a plus
Understanding of credit risk metrics like RWA, Expected loss, Regulatory and Economic capital, OTTI, Watchlist, Asset quality etc.
Conceptual understanding of the data and methodology used for credit risk regulatory models
Leveraging experiential know-how of a wide range of loan types, including C&I, CRE, RRE, ABL, Leasing, Credit Card, Vehicle, Personal etc.
Prior experience in domains like commercial banking, retail banking, treasury, investment management and strong knowledge of risk data analysis and development, strategy design and delivery deployment.
Vendor Experience
Experience in bureau data from credit unions e.g. D&B, Experian, Equifax, Transunion
Experience in vendor models and ratings like Fitch, Credit pro, Moody etc. o Knowledge about external / benchmark models on consumer portfolios is a plus (FICO Score, Standards and Poor’s, Fitch or Moody’s Ratings)
Selecting, implementing and/or using commercial credit risk workflow, analytics- e.g., Moody’s KMV, S&P and/or, reporting technologies- e.g., Oracle, Cognos, et al

Non-functional skill requirements: In order to succeed in PwC Risk CoE, it is desirable for candidates to possess:

Understanding of market trends and demands in the financial services sector and issues faced by clients by staying abreast of current business and industry trends relevant to the client’s business
Excellent oral and written communication skills
Solid analytical and problem-solving skills; ability to isolate and solve issues using large amounts of data
Process orientation with strong technical skills and attention to detail
Deep technical capabilities and industry knowledge of financial products
Willingness to travel to meet client needs, as needed

Educational Background: Desired candidate must have a master’s degree or higher in a quantitative discipline such as Economics, Statistics, Mathematics, Operation Research, Econometrics, Data Science, Finance, Engineering + MBA; advanced degree is a plus; Industry relevant certifications in CQF, FRM, CFA, CPA certification is a plus

Fitch Learning | Senior Inside Sales Executive, CQF – Toronto, Canada

Fitch Learning is a leader in financial services training. With unrivaled breadth and depth, the company delivers learning solutions for apprentices, graduates, and those with 10+ years’ experience in Financial Services. Our offerings include expert faculty, e-learning, coaching, and blended assessments, improving individual and collective business performance. Fitch Learning is a Fitch Solutions company.

Working at Fitch Learning provides the opportunity to be part of a global leader in financial education, committed to delivering cutting-edge training solutions. You’ll collaborate with a team of experts dedicated to empowering professionals with the skills and knowledge needed to excel in the finance industry. By joining us, you’ll be at the forefront of innovation in professional education, contributing to impactful learning experiences that drive career advancement and industry success.

Fitch Learning is seeking an Inside Sales Senior Associate for the CQF (Certificate in Quantitative Finance) program. This individual contributor role is based in our Toronto, Canada office, with a corporate title of Senior Associate.

About The Team

The CQF (Certificate in Quantitative Finance) is the world’s largest quant finance qualification. As a CQF Inside Sales Senior Associate, you will be responsible for selling the CQF program to warm leads generated by the marketing team, and for independently generating business opportunities.

You may be a fit for our team if you are looking to:

Earn a competitive base salary and benefits package, with 40% commissions for On Target Earnings—uncapped.
Be a vital contributor to a thriving global sales team.
Take full ownership of assigned sales leads in your region.

How You’ll Make An Impact

Manage and grow your sales pipeline, primarily through phone sales, email, and LinkedIn messaging to marketing-generated leads.
Sell complex solutions to a range of financial services professionals and aspiring professionals, including pitching to senior-level finance executives.
Drive attendance at CQF online information sessions and leverage these sessions to generate sales.
Build strong, value-added relationships with CQF alumni to generate referrals.
Participate in and follow up with attendees from conferences and talks (both online and in London) organized by the CQF.
Work collaboratively with the Marketing, Operations, and CQF Institute teams.
Attend industry events and conferences as required.
Track sales activity in key CRM systems.

You May be a Good Fit for this Role if:

You have proven B2C experience in training or delegate sales.
You are able to sell in a high-volume, metrics-driven environment.
You possess excellent lead management skills.

What Would Make You Stand Out

Proven experience selling technical “off-the-shelf” qualifications or training to individuals or corporate clients, preferable in the financial services industry.
Proficiency in phone sales and videoconferencing (e.g., Zoom or similar platforms).
Excellent presentation, conversational, and writing skills.

Why Choose Fitch

Hybrid Work Environment:3 days per week in the office; 2 days remote
A Culture of Learning & Mobility: Dedicated trainings, leadership development and mentorship programs designed to ensure that your time at Fitch will be a continuous learning opportunity
Investing in Your Future: Retirement planning and tuition reimbursement programs that empower you to achieve your short and long-term goals
Promoting Health & Wellbeing: Comprehensive healthcare offerings that enable physical, mental, financial, social, and occupational wellbeing
Supportive Parenting Policies: Family-friendly policies, including a generous global parental leave plan, designed to help you balance career and family life effectively
Inclusive Work Environment: A collaborative workplace where all voices are valued, with Employee Resource Groups that unite and empower our colleagues around the globe
Dedication to Giving Back: Paid volunteer days, matched funding for donations and ample opportunities to volunteer in your community