ZipRecruiter

Log In

1

Quantitative Portfolio Optimization Jobs (NOW HIRING)

ExxonMobil

Quantitative Analyst, V&S LNG

Spring, TX

Build analytical frameworks to assess LNG portfolio optimization opportunities across global gas ... Collaborate closely with quantitative analysts, technology teams, and data engineers to develop ...

ExxonMobil

Quantitative Analyst, V&S LNG

Spring, TX

Build analytical frameworks to assess LNG portfolio optimization opportunities across global gas ... Collaborate closely with quantitative analysts, technology teams, and data engineers to develop ...

ExxonMobil

Quantitative Analyst, V&S LNG

Spring, TX · On-site

Build analytical frameworks to assess LNG portfolio optimization opportunities across global gas ... Collaborate closely with quantitative analysts, technology teams, and data engineers to develop ...

Nomura International

Quant Researcher

Manhattan, NY · On-site

$175K - $250K/yr

This role focuses on quantitative modeling, risk management, and portfolio optimization to support our global equities business. Key Responsibilities Risk Modeling & Portfolio Optimization * Design ...

previous pagenext page

Showing results 21-40

All JobsQuantitative Portfolio Optimization Jobs

Quantitative Portfolio Optimization information

See salary details

$98K

$169.7K

$259.5K

How much do quantitative portfolio optimization jobs pay per year?

As of Aug 14, 2026, the average yearly pay for quantitative portfolio optimization in the United States is $169,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $199,000.00 per year, depending on experience, location, and employer.

What is quantitative portfolio optimization?

Quantitative portfolio optimization is the process of using mathematical models and statistical techniques to construct investment portfolios that maximize expected returns for a given level of risk, or minimize risk for a given level of expected return. This approach relies on quantitative data analysis, such as historical prices, returns, and correlations between assets, to inform the portfolio construction process. Techniques like mean-variance optimization, factor models, and Monte Carlo simulations are commonly used. The goal is to systematically select asset weights that best align with an investor's financial objectives and risk tolerance.

What are the key skills and qualifications needed to thrive as a quantitative portfolio optimization specialist?

To thrive in Quantitative Portfolio Optimization, you need strong quantitative analysis skills, advanced knowledge of statistics and finance, and typically a degree in mathematics, finance, or a related field. Expertise in programming languages like Python, R, or MATLAB, and familiarity with financial modeling tools and data analytics platforms are commonly required. Attention to detail, critical thinking, and effective communication are essential soft skills for interpreting data and collaborating with stakeholders. These skills ensure the development of robust, data-driven investment strategies that maximize returns and minimize risk.

What are some common challenges faced by professionals in quantitative portfolio optimization, and how can they be addressed?

Professionals in Quantitative Portfolio Optimization often encounter challenges such as managing large and complex datasets, adapting to rapidly changing market conditions, and balancing risk versus return in real time. Staying current with the latest financial models and programming techniques is essential, as is collaborating closely with portfolio managers and data scientists to ensure that optimization strategies align with investment goals. Building strong analytical and communication skills can help address these challenges and contribute to more effective decision-making within the team.

What is the difference between Quantitative Portfolio Optimization vs Quantitative Analyst?

AspectQuantitative Portfolio OptimizationQuantitative Analyst
Primary FocusDeveloping models to optimize investment portfolios for risk and returnAnalyzing data to support investment decisions and strategy
Skills & CertificationsMathematics, statistics, programming, finance certifications (CFA, FRM)Statistics, programming, finance knowledge, often CFA or similar
Work EnvironmentQuant teams within asset management or hedge fundsInvestment banks, asset managers, hedge funds
GoalsMaximize portfolio performance while managing riskProvide insights and analysis to inform investment strategies

While both roles require strong quantitative skills and finance knowledge, Quantitative Portfolio Optimization focuses specifically on creating models to optimize investment portfolios, whereas a Quantitative Analyst provides broader data analysis and insights to support investment decisions.

More about Quantitative Portfolio Optimization jobs

What job categories do people searching Quantitative Portfolio Optimization jobs look for?

The top searched job categories for Quantitative Portfolio Optimization jobs are:

Infographic showing various Quantitative Portfolio Optimization job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 89% Full Time, 7% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $169,729 per year, or $81.6 per hour.

Quantitative Researcher - Portfolio Optimization - Jersey City, NJ

Stevens Capital Management LP

Jersey City, NJ • On-site

$150K - $300K/yr

Full-time

Medical, Dental, Retirement

Re-posted 19 days ago

Job description

SCM is committed to a workplace that values and promotes diversity, inclusion and equal employment opportunity by ensuring that all employees are valued, heard, engaged and involved at work and have full opportunities to collaborate, contribute and grow professionally.
Primary Responsibilities:
  • Design and implement multi-period portfolio optimization frameworks incorporating
    transaction costs, slippage, and other market frictions
  • Leverage MOSEK and other optimization solvers to build scalable and efficient models
  • Develop and refine intraday trading strategies and execution algorithms
  • Monitor and analyze model performance in a live trading environment

Requirements:
  • Strong quantitative background (PhD or Master's in Applied Math, Operations Research, Computer Science, or related field)
  • Proven experience with MOSEK or other optimization frameworks
  • Deep understanding of slippage, transaction cost modeling, and intraday trading
  • Familiarity with real-time data processing and execution systems
  • Programming skills in Python and/or C++
  • Experience integrating optimization routines in production trading systems

The base pay for this position is anticipated to be between $150,000 and $300,000 per year. The anticipated annual base pay range is current as of the time this job post was generated. This position is eligible for other forms of compensation and benefits, such as a bonus, health and dental plans and 401(k) contributions, which includes a discretionary profit sharing program. An employee's bonus and related compensation benefits can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.

Apply