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Quantitative Engineer Jobs (NOW HIRING)

Jay Analytix

Quantitative Developer

New York, NY · Hybrid

Quantitative Developer Location: New York, USA - Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance and advanced ...

Jay Analytix INC.

Quantitative Developer

Manhattan, NY · On-site

Quantitative Developer Location: New York, USA -- Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance and advanced ...

Jay Analytix

Quantitative Developer

Jersey City, NJ · On-site

Quantitative Developer Location: New Jersey, Jersey City, USA Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance and ...

Jay Analytix Inc

Quantitative Developer

Jersey City, NJ · On-site

Quantitative Developer Location: New Jersey, Jersey City, USA - Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance ...

Jay Analytix

Quantitative Developer

Manhattan, NY · On-site

Quantitative Developer Location: New York, USA -- Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance and advanced ...

Jay Analytix Inc

Quantitative Developer

New York, NY · On-site

Quantitative Developer Location: New York, USA - Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance and advanced ...

Jay Analytix

Quantitative Developer

Jersey City, NJ · Hybrid

Quantitative Developer Location: New Jersey, Jersey City, USA - Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance ...

Jay Analytix

Quantitative Developer

New York, NY · On-site

Quantitative Developer Location: New York, USA Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance and advanced ...

Jay Analytix

Quantitative Developer

Jersey City, NJ · On-site

Quantitative Developer Location: New Jersey, Jersey City, USA -- Hybrid Employment Type: Contract About the Role We are seeking a Quantitative Developer with strong expertise in quantitative finance ...

IMC

Quantitative Developer - Derivatives

Chicago, IL · On-site

We're looking for a Quantitative Developer - Derivatives to join our Chicago office. At IMC, the Pricing and Risk (PAR) team owns the firm's core quantitative library for live derivatives pricing and ...

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Quantitative Engineer information

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How much do quantitative engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for quantitative engineer in the United States is $90,538.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,500.00 and $100,000.00 per year, depending on experience, location, and employer.

What is a quantitative engineer?

Quantitative Engineers, often called 'quants', are professionals who apply advanced mathematical, statistical, and programming skills to solve complex problems in finance, technology, or research. They develop models and algorithms to analyze data, assess risk, and inform decision-making, particularly in areas like trading, asset management, and financial engineering. Their work often involves programming in languages such as Python, C++, or R, and requires a strong background in mathematics and computer science. Quantitative Engineers play a crucial role in optimizing processes and strategies using quantitative methods.

What are the key skills and qualifications needed to thrive as a quantitative engineer, and why are they important?

To thrive as a Quantitative Engineer, you need a strong background in mathematics, statistics, and computer science, typically with a degree in a quantitative field such as math, physics, or engineering. Familiarity with programming languages like Python, C++, and tools such as MATLAB, as well as experience with data analysis frameworks, is essential. Exceptional problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly set top performers apart. These skills are crucial for developing robust quantitative models and algorithms that drive informed financial or technical decision-making.

How do quantitative engineers typically collaborate with traders and software developers in a financial firm?

Quantitative Engineers often work closely with traders to understand their strategies and translate them into mathematical models or algorithms. They also partner with software developers to ensure these models are efficiently implemented in trading platforms, balancing performance and accuracy. Regular communication and joint problem-solving are essential, as the role requires aligning complex quantitative methods with practical trading objectives and robust technical solutions.

What is the difference between Quantitative Engineer vs Quantitative Analyst?

AspectQuantitative EngineerQuantitative Analyst
CredentialsDegree in Math, Finance, or Engineering; often requires programming skillsDegree in Finance, Economics, or Math; strong analytical skills
Work EnvironmentDevelops models, writes code, collaborates with tech teamsAnalyzes data, creates reports, supports trading strategies
Industry UsageFinancial firms, hedge funds, investment banksAsset management, investment firms, banks

While both roles involve quantitative skills, Quantitative Engineers focus on developing and implementing models and algorithms, often requiring programming expertise. Quantitative Analysts primarily analyze data and support trading decisions. The roles are complementary but differ in technical depth and focus.

What do quantitative engineers do?

Quantitative engineers develop mathematical models and algorithms to analyze financial data, manage risk, and inform trading strategies. They often use programming languages like Python or C++ and work closely with traders and analysts in finance or technology firms. Strong skills in mathematics, statistics, and programming are essential for this role.
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Quantitative Engineer jobs near you
Infographic showing various Quantitative Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $90,538 per year, or $43.5 per hour.

Prediction Markets Quantitative Engineer

New York, NY • On-site

G-20 Group
See more jobs at G-20 Groupexternal

Full-time

Re-posted 5 days ago

Job description

About G20 Group
G-20 Group is a cross-asset trading firm headquartered in Switzerland, trading delta-one and derivatives markets globally. We combine startup agility with institutional-grade experience in proprietary trading, technology, and quantitative finance.
Role Overview
We are hiring a Prediction Markets Quant Engineer to build research and trading infrastructure for operating in prediction markets (event contracts) across multiple venues. You will design models that estimate event probabilities, detect mispricing, size positions, and manage risk - then translate them into reliable systems that run end-to-end (data → forecasting → execution → monitoring).
This role sits at the intersection of quant research, engineering, and market microstructure, and is ideal for someone who enjoys shipping robust systems as much as developing models.
Responsibilities
Modeling & Research
  • Develop probabilistic models to forecast outcomes of real-world events (e.g., elections, macro releases, sports, policy decisions, industry milestones).
  • Combine heterogeneous signals (time series, text/news, market data, polling/alternative data, fundamentals, expert priors) into calibrated probability estimates.
  • Build pricing and edge frameworks: fair value, uncertainty bands, expected value, and model drift/regime diagnostics.
  • Design evaluation methods (proper scoring rules like log loss/Brier score, calibration curves, back-tests with realistic costs and constraints).

Trading & Market Design (Applied)
  • Identify and exploit mis-pricings across contracts/venues; design cross-market arbitrage and relative-value strategies where feasible.
  • Build position sizing and risk frameworks (Kelly variants, drawdown/risk budgets, scenario stress tests, liquidity/impact-aware sizing).
  • For multi-outcome markets: enforce probability coherence (no-arb constraints, normalization) and portfolio optimization across correlated contracts.

Engineering & Production
  • Build data pipelines and real-time services for ingesting, cleaning, and versioning market + external data.
  • Implement execution tooling: order management, smart routing (where applicable), monitoring, and automated safeguards.
  • Create dashboards/alerts for performance, exposure, model health (calibration, drift), and operational integrity.
  • Ensure reproducibility: experiment tracking, model registry, CI/CD, and robust testing.

Collaboration & Governance
  • Work closely with trading/risk/compliance stakeholders to translate research into controlled deployment.
  • Document models, assumptions, failure modes, and operating procedures; participate in incident reviews and continuous improvement.

Requirements
  • Degree in Quantitative Finance, Mathematics, Computer Science, Statistics, or a related quantitative field.
  • Strong engineering skills with Python (required); experience with production systems and data engineering.
  • Solid foundation in statistics, probability, and machine learning (calibration, uncertainty, causal pitfalls, time-series).
  • Experience building backtests and evaluating predictive models with appropriate metrics (e.g., log loss/Brier, calibration).
  • Familiarity with trading concepts: expected value, position sizing, risk budgeting, correlation, liquidity constraints.
  • Ability to communicate clearly about model assumptions, limitations, and risk.
  • Some schedule flexibility may be required around major event windows
  • Self-motivated, detail-oriented, and comfortable working in a dynamic, startup-like environment.

Preferred / Desirable Experience
  • Prior work in forecasting, sports analytics, political modeling, event-driven trading, or market-making/liquidity modeling.
  • Experience with NLP for news/social/media signals; knowledge graphs or information retrieval for event resolution.
  • Knowledge of prediction market mechanics (order books vs AMMs, fee structures, market manipulation/anti-manipulation signals).
  • Proficiency with SQL; experience with streaming systems (Kafka), workflow orchestration (Airflow), and cloud (AWS/GCP/Azure).
  • Experience with Bayesian methods, probabilistic programming (Stan/PyMC), or ensemble methods.
  • Familiarity with rigorous experimentation: online/offline evaluation, data leakage prevention, and model governance.

Tech Stack
  • Python, SQL, pandas/numpy/scipy, PyTorch/sklearn
  • Airflow/dbt, Kafka (or equivalents), Postgres/BigQuery
  • Docker, Kubernetes (optional), CI/CD (GitHub Actions)
  • Observability: Prometheus/Grafana, OpenTelemetry (or equivalents)

Locations and Right to work: This role can be based out of our Zurich, London, New York or Hong Kong office. Only candidates who possess the pre-existing right to work in one of the locations above without company sponsorship need apply.
Join G-20 and be a part of a team that is at the forefront of financial markets, driving innovation and excellence in the sector.

Apply