Remote Lead Data Scientist - Algorithmic Trading

Placements24; East London; Hybrid; ZAR 1,800,000 - 3,000,000; Full time

Job summary

Placements24 is seeking a Lead Data Scientist specializing in Algorithmic Trading to lead a remote research team. You will mentor researchers, design ML models, and deploy predictive trading strategies in a fast-paced, high-stakes environment.

The role demands a PhD or MSc in a quantitative field, 7+ years in data science with finance exposure, strong Python/C++, and cloud experience. You’ll influence investment decisions and drive innovation across the firm’s data infrastructure.

Qualifications

• PhD or MSc in Computer Science, Statistics, Math, Physics or related field.
• 7+ years in data science with strong finance/quant trading exposure.
• Expert Python/C++ skills and ML libraries.

Responsibilities

• Lead R&D of data-driven algo trading strategies.
• Design and test ML models for prediction and alpha generation.
• Build scalable data pipelines and feature engineering.
• Collaborate with researchers and traders to deploy models live.
• Mentor junior data scientists and researchers.

Skills

Python

C++

ML

Data pipelines

Cloud (AWS)

Leadership

Research methods

Finance/Quant

Education

PhD or MSc in quantitative field

Tools

scikit-learn

TensorFlow

PyTorch

AWS

GCP

Job description

About the Role

Our client, a highly successful quantitative hedge fund, is seeking an exceptional Lead Data Scientist with a specialization in Algorithmic Trading to join their elite, fully remote research team. This is a unique opportunity to leverage advanced machine learning techniques and big data analytics to develop and enhance cutting-edge trading strategies. You will lead a small team of data scientists, mentor junior researchers, and drive innovation in a fast-paced, intellectually stimulating environment. This role is entirely remote, allowing you to contribute from anywhere in the world while collaborating with world-class talent. We are looking for a visionary leader with a proven track record in applying data science to financial markets, exceptional coding skills, and a passion for quantitative research.

Key Responsibilities

• Lead the research and development of data-driven algorithmic trading strategies.
• Design, implement, and test sophisticated machine learning models for prediction, pattern recognition, and alpha generation.
• Analyze vast datasets of historical and real-time market data to extract actionable insights.
• Develop and optimize data pipelines and feature engineering techniques for trading models.
• Collaborate closely with quantitative researchers and traders to integrate models into live trading systems.
• Mentor and guide junior data scientists and researchers, fostering technical growth and collaboration.
• Evaluate the performance of trading strategies and identify areas for improvement.
• Stay abreast of the latest advancements in machine learning, artificial intelligence, and financial econometrics.
• Contribute to the development of the firm's data infrastructure and analytical tooling.
• Present research findings and strategy performance to senior management and investment committees.

Requirements

• PhD or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or a related discipline.
• 7+ years of experience in data science, with a significant focus on quantitative finance or algorithmic trading.
• Expert-level proficiency in Python and/or C++, including relevant libraries for data science and machine learning (e.g., scikit-learn, TensorFlow, PyTorch).
• Deep understanding of statistical modeling, machine learning algorithms, and financial econometrics.
• Experience working with large, complex financial datasets and high-frequency trading data.
• Proven ability to lead research projects and mentor technical teams.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex concepts clearly.
• Experience with cloud platforms (AWS, Azure, GCP) and big data technologies is a plus.
• Demonstrated success in developing and deploying predictive models in a trading context.

Benefits

• Extremely competitive salary and generous performance-based bonuses.
• Significant equity participation and long-term incentive plans.
• Comprehensive health, dental, and vision insurance coverage.
• 401(k) plan with substantial employer match.
• Unlimited vacation policy and flexible remote work options.
• Home office setup budget and ongoing technology stipends.
• Access to state-of-the-art research infrastructure and cutting-edge technology.
• Intellectually challenging work with a direct impact on investment performance.