Quantitative Researcher

Goliath Partners; New York (NY); Remote; USD 900,000 - 1,100,000; Full time

Job summary

Goliath Partners Inc. is seeking a Quantitative Researcher to join a leading systematic trading team. You will build original alpha signals, develop predictive models, and push research from hypothesis through backtesting and live deployment.

You’ll apply advanced statistics and ML for short-horizon forecasting on equities and futures, evaluate signals against costs and market impact, and collaborate with fellow researchers to turn findings into scalable trading strategies.

Qualifications

• 1-7 years of quantitative research experience with contributions to equities alpha or systematic strategies.
• Experience building predictive models from scratch for financial markets.
• A research publication record with an h-index of 10 or higher.
• Strong Python skills; C++ experience is a plus.
• Bachelor’s, Master’s, or PhD in CS, Applied Mathematics, Statistics, Engineering, or related discipline.

Responsibilities

• Develop original alpha signals and predictive models, from initial hypothesis through backtesting and live deployment.
• Apply statistical and ML techniques to short-horizon forecasting across equities and futures.
• Evaluate signals against transaction costs, market impact, and out-of-sample robustness.
• Work closely with fellow researchers to turn promising findings into systematic trading strategies.

Skills

Python

C++

Machine Learning

Statistics

Education

CS/Applied Mathematics/Statistics/Engineering degree

Tools

Backtesting frameworks

Job description

Flexible US location Non-competes accommodated

Build original predictive models and see your research through to live trading.

Goliath is partnering with a leading systematic investment and trading firm to hire a Quantitative Researcher for its established intraday and mid-frequency equities and futures business.

You’ll join a selective, collaborative research team developing new statistical and machine-learning approaches to alpha generation. The opportunity combines meaningful individual research contributions with extensive datasets, substantial computing resources, and sophisticated trading infrastructure.

The work

• Develop original alpha signals and predictive models, from initial hypothesis through backtesting and live deployment.
• Apply statistical and ML techniques to short-horizon forecasting across equities and futures.
• Evaluate signals against transaction costs, market impact, and out-of-sample robustness.
• Work closely with fellow researchers to turn promising findings into systematic trading strategies.

What you’ll bring

• Approximately 1-7 years of quantitative research experience, with clear contributions to equities alpha or systematic strategies.
• Experience building predictive models from scratch, ideally for financial markets.
• A research publication record with an h-index of 10 or higher.
• Strong Python skills; C++ experience is a plus.
• A bachelor’s, master’s, or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or a related discipline.

Experience in deep learning, statistical arbitrage, or research that has improved live trading outcomes is particularly relevant.

Compensation: $1M-$3M total compensation, depending on experience and team fit.

Location: Flexible within the US.

Timing: The firm is willing to wait through non-competes.