Lead Data Scientist - Algorithmic Trading

Placements24; Rustenburg; Hybrid; ZAR 3,005,000 - 4,007,000; Full time

Benefits offered by this job

Stock options

Profit-sharing

Fully remote work arrangement

Generous annual leave

Professional development budget

Wellness benefits

Job summary

Placements24 is seeking a Lead Data Scientist for a remote, senior role in a cutting-edge FinTech environment. You will design, develop, and deploy ML models powering trading algorithms, and lead a team of data scientists and engineers.

You will apply deep knowledge of quantitative finance, time series modeling, and scalable data pipelines in a fast-paced, remote-first setting. Strong collaboration with researchers and software engineers is essential, as is delivering production-ready code and

Qualifications

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, Quantitative Finance, or a related field.
• 7+ years of experience in data science, machine learning, and statistical modelling, with focus on financial markets or algorithmic trading.
• Proven track record of developing and deploying ML models in production.
• Strong programming skills in Python and libraries such as Pandas, NumPy, SciPy, Scikit-learn, TensorFlow/PyTorch.
• Expertise in time series analysis, statistics, and ML algorithms including regression, classification, clustering, and deep learning.
• Experience with big data technologies (Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Excellent understanding of financial markets, trading strategies, and financial instruments.
• Strong problem-solving and independent work ability in remote settings.
• Exceptional communication and collaboration skills for remote teams.
• Experience leading technical teams is essential.

Responsibilities

• Lead the design, development, and implementation of ML algorithms and models for algorithmic trading strategies.
• Analyze large, complex datasets of financial market data to identify predictive patterns.
• Develop and optimize data pipelines and infrastructure for real-time trading systems.
• Collaborate with quantitative researchers to translate ideas into production-ready code.
• Mentor and guide a team of data scientists, fostering innovation and excellence.
• Evaluate and implement new data science methods, tools, and technologies.
• Monitor deployed models and systems, addressing issues proactively.
• Present findings and recommendations to senior management.
• Contribute to strategic direction of the data science team and firm’s tech advances.
• Ensure scalability, reliability, and efficiency of data science solutions.

Skills

Leadership

Remote collaboration

Analytical thinking

Problem solving

Education

Master's or PhD in CS/Statistics/Math/Physics/Quantitative Finance

Tools

Python

Pandas/Numpy/SciPy/Scikit-learn

TensorFlow/PyTorch

Spark/Hadoop

AWS/Azure/GCP

Job description

About the Role

Our client, a cutting-edge FinTech firm renowned for its innovative approach to algorithmic trading, is looking for a highly experienced and visionary Lead Data Scientist to spearhead their data science initiatives. This is a fully remote, senior position, offering the unique opportunity to shape the future of high-frequency trading strategies from anywhere in the world. You will be responsible for designing, developing, and deploying advanced machine learning models and data-driven solutions that power our trading algorithms. This role demands a deep understanding of quantitative finance, statistical modeling, and programming expertise. You will lead a talented team of data scientists and collaborate closely with quantitative researchers and software engineers to push the boundaries of financial technology. This remote-first role is ideal for a self-motivated individual who thrives in a collaborative, virtual environment and is passionate about leveraging data to drive market success.

Key Responsibilities

• Lead the design, development, and implementation of sophisticated machine learning algorithms and statistical models for algorithmic trading strategies.
• Analyze large, complex datasets of financial market data to identify predictive patterns and trading opportunities.
• Develop and optimize data pipelines and infrastructure to support real-time trading systems.
• Collaborate with quantitative researchers to translate trading ideas into production-ready code.
• Mentor and guide a team of data scientists, fostering a culture of innovation and technical excellence.
• Evaluate and implement new data science methodologies, tools, and technologies.
• Monitor the performance of deployed models and systems, identifying and addressing any issues proactively.
• Present findings and recommendations to senior management and stakeholders.
• Contribute to the strategic direction of the data science team and the firm's technological advancements.
• Ensure the scalability, reliability, and efficiency of all data science solutions.

Requirements

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Physics, Quantitative Finance, or a related field.
• Extensive experience (7+ years) in data science, machine learning, and statistical modelling, with a significant portion focused on financial markets or algorithmic trading.
• Proven track record of developing and deploying successful machine learning models in production environments.
• Expert-level programming skills in Python (and relevant libraries like Pandas, NumPy, SciPy, Scikit-learn, TensorFlow/PyTorch).
• Strong knowledge of time series analysis, statistical modelling, and machine learning algorithms (e.g., regression, classification, clustering, deep learning).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
• Excellent understanding of financial markets, trading strategies, and financial instruments.
• Strong problem-solving skills and the ability to work independently in a remote setting.
• Exceptional communication and interpersonal skills for effective remote collaboration.
• Experience leading technical teams is essential for this role.

Benefits

• Highly competitive salary and substantial performance-based bonuses.
• Stock options and profit-sharing opportunities.
• Fully remote work arrangement with flexible hours.
• Generous annual leave and paid time off.
• Budget for professional development, conferences, and training.
• Access to state-of-the-art technology and research tools.
• Comprehensive health and wellness benefits package.
• Opportunity to work on challenging and impactful projects at the forefront of FinTech.