100 Matawan Road, Suite 325, Matawan, NJ, 07747

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Mon-Sat, 8am-6pm By Appointment on Weekend

+1 (848) 373-1200

  • Full Time
  • NYC - Onsite
  • $150K + Benefits USD / Year

Job Title: Data Scientist – Predictive Modeling / Capital Markets
Location: Onsite – Manhattan, NY (5 days/week)
Employment Type: Full-Time Consultant (W-2)
Compensation: $150,000 Base + Health Benefits, PTO, Vacation, and 401(k) with 3% Match
Client Industry: Hedge Fund / Capital Markets

About the Role

Our Client, is seeking a sharp, mathematically minded Data Scientist to join our high-performance consulting practice serving one of the most sophisticated hedge funds in the world. This is a full-time, onsite position based in Manhattan, NY, working in a highly quantitative, data-intensive trading environment.

The ideal candidate combines deep statistical knowledge, advanced Python proficiency, and a track record in predictive modeling or machine learning applications. Experience in capital markets, particularly with equities data or trading strategies, is a strong plus but not strictly required.

This is an opportunity to apply scientific rigor and modern AI/ML techniques to solve real-world financial problems in a mission-critical environment.

Key Responsibilities

  • Build, validate, and deploy predictive models to support trading, research, or risk use cases.
  • Design and execute machine learning pipelines using Python and related libraries (scikit-learn, XGBoost, TensorFlow, PyTorch, etc.).
  • Work directly with quants, traders, and analysts to turn data into actionable insights and real-time decision systems.
  • Collaborate with data engineering teams to ensure clean, reliable, and high-frequency access to structured and unstructured data sources.
  • Analyze complex market behaviors, patterns, and signals using rigorous statistical and mathematical techniques.
  • Conduct research experiments, test hypotheses, and deliver presentations to technical and non-technical stakeholders.
  • Contribute to model monitoring, drift detection, retraining strategies, and performance evaluation in live environments.

Required Qualifications

  • Master’s degree in Mathematics, Statistics, Physics, Game Theory, Computer Science, or a related science/engineering discipline.
  • 3+ years of experience applying data science, predictive modeling, or AI/ML in a professional setting.
  • Strong command of Python for data manipulation, statistical analysis, and model building.
  • Solid understanding of supervised/unsupervised learning, time series analysis, and feature engineering.
  • Comfortable working with large and complex datasets using tools like Pandas, NumPy, SQL, and cloud-based platforms.
  • Experience delivering production-grade models and collaborating with engineering teams on deployment.
  • Exceptional analytical skills and the ability to think probabilistically and work in ambiguity.

Preferred Experience

  • Experience in capital markets, especially in equities, systematic strategies, or alpha research.
  • Familiarity with financial data sources such as Bloomberg, Refinitiv, or Quandl.
  • Exposure to portfolio construction, risk modeling, or execution optimization frameworks.
  • Background in game theory, agent-based modeling, or optimization problems is a strong plus.
  • Prior work in high-frequency, real-time, or trading environments.

Work Environment

This is a 100% onsite role (5 days/week) at the client’s Manhattan office. As a consultant with Our Client , you will represent an elite delivery team embedded within a hedge fund setting, with full access to institutional-grade data, technology, and business expertise.

Why Join Our Client ?

  • Work with top-tier financial clients and world-class technologists
  • Competitive compensation and a full benefits package
  • Exposure to advanced ML, quant research, and data engineering practices
  • Culture of intellectual rigor, collaboration, and continuous learning
  • Long-term engagement opportunities with room for professional growth

To apply for this job email your details to info@cr-inc.com