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Quantitative Researcher

Time Zone
Department

Global

Seniority Level

Research

Employment Type

Mid-Level

Full-time

Summary

Join Exponential Technology as a Quantitative Researcher developing proprietary predictive signals and analytics across equities, options, futures, and macroeconomic data. You will apply rigorous quantitative methods — statistical modeling, machine learning, and time-series analysis — to extract actionable intelligence from large-scale financial datasets. This role sits at the intersection of financial theory and applied mathematics: you will design, backtest, and validate research that directly powers ETI’s data products for institutional investors.

Day to Day Responsibilities

  • Design and implement quantitative models for predictive signal generation across equities, options, futures, and macro asset classes.
  • Conduct rigorous statistical analysis on large-scale financial datasets to identify patterns, anomalies, and tradeable signals.
  • Build and maintain backtesting frameworks to validate signal efficacy, measure alpha decay, and assess out-of-sample performance.
  • Develop and refine factor models, risk models, and attribution frameworks for ETI’s data products.
  • Collaborate with the engineering team to productionize research outputs into scalable, real-time data pipelines.
  • Perform exploratory data analysis on new datasets to assess commercial value and integration feasibility.
  • Write clear, reproducible research documentation and present findings to stakeholders.
  • Monitor live signal performance, diagnose degradation, and iterate on model improvements.

AI and Automation Responsibilities

  • Leverage LLM-based research tools to accelerate literature review, data exploration, and hypothesis generation.
  • Use AI coding assistants (Claude Code, Windsurf, Cursor) to accelerate model development, backtesting, and data pipeline construction.
  • Design Agentic AI workflows for automated signal monitoring, performance reporting, and anomaly detection.
  • Evaluate and integrate emerging AI/ML frameworks for feature engineering, model selection, and hyperparameter optimization.

Requirements

  • Master’s degree (required) in Quantitative Finance, Financial Mathematics, Financial Engineering, Statistics, Applied Mathematics, Physics, or a related engineering discipline. PhD preferred.
  • Strong foundation in probability theory, stochastic calculus, statistical inference, and time-series analysis.
  • Demonstrated experience building quantitative models for financial markets — signal research, factor models, risk models, or systematic trading strategies.
  • Proficiency in Python for quantitative research (NumPy, pandas, scikit-learn, statsmodels). Additional languages (C++, R) valued.
  • Experience with large-scale financial datasets: tick data, order book data, corporate actions, reference data, and macroeconomic indicators.
  • Significant financial services experience — direct exposure to institutional investment, trading, portfolio management, or quantitative research.

Cultural Fit - Who Trives at Exponential

  • High Executive Functioning Skills — Ability to plan, prioritize, organize, and execute complex research independently.

  • Excellent Communicator — Able to articulate quantitative concepts to non-technical stakeholders.

  • Team Player — Collaborative, ego-free contributor who elevates others.

  • Continuous Learner — Willingness and demonstrated habit of continuously learning new methods and reading academic papers.

  • Critical Thinker — Questions assumptions and proposes well-reasoned solutions.

  • Composure Under Pressure — Maintains calm under tight deadlines and ambiguity.

Would Be Great If You Also Have Exposure To

  • Apache Arrow for high-performance data processing in research pipelines.

  • Real-time streaming analytics and event-driven architectures.

  • Options pricing models, volatility surface modeling, and Greeks computation.

  • Natural Language Processing applied to financial text (earnings calls, filings, news).

  • Alternative data sources and their integration into quantitative research.

  • Experience publishing research or presenting at quantitative finance conferences.

  • Familiarity with high-performance computing: parallel processing, GPU acceleration, or distributed computation.

Compensation

  • Competitive base salary commensurate with experience and credentials.

  • Stock option grant — participate in ETI’s growth as a pre-Series A team member.

  • Performance-based cash bonuses tied to research impact and product outcomes.

About Exponential Technology

At Exponential, we empower enterprises to innovate more rapidly by leveraging on-prem and on-cloud data technology in combination with tightly integrated analytics and LLM toolsets. By integrating data into a high-performance and flexible data backplane, we help businesses of all sizes overcome data entropy and unlock their true analytical capacity as an organization. With over 25 years of experience in the institutional investment space, we leverage our knowledge to extract value from data with our State-of-the-Art Technology and Analytics stack.


We are an AI-native company. Every team member — from engineering to marketing to operations — uses Agentic AI and AI-powered tools daily. If you are excited about working at the frontier of AI-augmented productivity in financial data technology, we want to hear from you.

How to Apply

Send your resume and cover letter to hr@exponential-tech.ai with the job title in the email subject line.

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