Lead Data Scientist, Algorithmic Trading

Placements24; Vereeniging; Hybrid; ZAR 1,500,000 - 2,300,000; Full time

Benefits offered by this job

High salary potential

Bonuses and profit sharing

Health, dental, and vision insurance

Equity opportunity

Remote-first culture

Conference support

Job summary

Placements24 invites a Lead Data Scientist to join a cutting-edge quantitative trading team. This remote role focuses on designing, developing, and deploying advanced ML models and trading algorithms across asset classes.

You will mentor junior scientists, collaborate with PMs and engineers, and build back-testing frameworks to evaluate performance, while staying at the forefront of quantitative finance. Candidates should hold a PhD or MSc, 5+ years in data science with finance experience, and

Qualifications

• PhD or Master’s in Computer Science, Statistics, Mathematics, Physics, or related quantitative field.
• 5+ years of hands-on data science experience with a focus on algorithmic trading or quantitative finance.
• Proven track record of developing and deploying ML models in trading contexts.
• Strong Python and data science libraries (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).

Responsibilities

• Lead the design and implementation of ML models and statistical algorithms for algorithmic trading.
• Analyze large financial datasets to identify predictive signals and opportunities.
• Develop and maintain back-testing frameworks to evaluate strategies.
• Collaborate with software engineers to deploy trading algorithms to production.
• Mentor junior data scientists and researchers.
• Stay at the forefront of ML, AI, and quantitative finance.

Skills

Python

Time series analysis

Machine learning

Critical thinking

Remote collaboration

Education

PhD or Master’s in a quantitative field

Tools

NumPy

Pandas

Scikit-learn

TensorFlow

PyTorch

Spark/Hadoop

Job description

About the Role

Our client, a cutting-edge quantitative trading firm, is seeking an exceptional Lead Data Scientist to spearhead their Algorithmic Trading division. This is a fully remote, highly influential position requiring a blend of deep technical expertise in data science and machine learning, combined with a strong understanding of financial markets. You will be instrumental in designing, developing, and deploying sophisticated algorithms that drive our trading strategies across various asset classes. Operating in a remote-first environment, you will collaborate closely with portfolio managers, software engineers, and other data scientists to push the boundaries of quantitative finance. This role offers a unique opportunity to shape the future of algorithmic trading and to work on challenging problems with significant impact. We foster a culture of innovation, intellectual curiosity, and continuous learning, all within a fully distributed team structure. If you are passionate about uncovering insights from vast datasets and translating them into profitable trading strategies, this role is for you.

Key Responsibilities

• Lead the research, design, and implementation of advanced machine learning models and statistical algorithms for algorithmic trading strategies.
• Analyze large, complex datasets from various financial markets to identify predictive signals and trading opportunities.
• Develop and maintain robust back-testing frameworks to evaluate strategy performance.
• Collaborate with software engineers to deploy trading algorithms into production environments.
• Mentor and guide junior data scientists and researchers.
• Stay at the forefront of advancements in machine learning, AI, and quantitative finance.
• Communicate complex technical findings and strategy recommendations to stakeholders in a clear and concise manner.
• Contribute to the firm's intellectual property through novel research and development.

Requirements

• PhD or Master's degree in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• 5+ years of hands-on experience in data science, with a significant focus on algorithmic trading or quantitative finance.
• Proven track record of developing and deploying successful machine learning models in a trading context.
• Expertise in Python and relevant data science libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).
• Strong understanding of time series analysis, statistical modeling, and optimization techniques.
• Experience with big data technologies (e.g., Spark, Hadoop) is advantageous.
• Excellent problem-solving, analytical, and critical thinking skills.
• Ability to thrive in a fast-paced, remote, and collaborative team environment.
• Strong communication skills, able to articulate complex ideas effectively.

Benefits

• An industry-leading annual salary of R.
• Exceptional performance-based bonuses and profit sharing.
• Full health, dental, and vision insurance coverage.
• Generous allocation of company equity.
• Unlimited opportunities for professional growth and learning.
• Fully remote work environment with flexible hours.
• State-of-the-art technology and research resources.
• Support for attending leading conferences and workshops.