Lead Data Scientist - AI/ML

Placements24; Cape Town; Hybrid; ZAR 1,000,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive medical cover

Equity participation

Budget for professional development

Fully remote setup

Job summary

Placements24 is seeking a Lead Data Scientist to spearhead AI/ML initiatives in Cape Town, with a fully remote setup across South Africa.

You will lead a team of data scientists and engineers, build production-grade models, shape the data strategy, and translate analytics into measurable business outcomes.

The role offers a competitive salary, comprehensive benefits, equity participation, and strong commitments to professional development.

Qualifications

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of experience in data science or machine learning, with at least 2 years in a leadership role.
• Proven track record of developing and deploying ML models in production.
• Experience with Python or R and relevant libraries (TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of statistical modeling, data mining, and ML algorithms.

Responsibilities

• Lead the design, development, and deployment of advanced ML models and AI solutions.
• Manage and mentor a team of data scientists, providing technical guidance.
• Collaborate with stakeholders to translate business requirements into analytical projects.
• Develop and maintain data pipelines ensuring data quality and accessibility.
• Stay updated on AI/ML advancements and incorporate new technologies.
• Present findings and recommendations to technical and non-technical audiences.

Skills

Leadership

Mentoring

Data strategy

Communication

Problem solving

Education

Master's or PhD in CS/Math/Statistics

Tools

TensorFlow

PyTorch

Scikit-learn

Spark

Hadoop

Cloud platforms

Job description

About the Role

Our client is seeking a highly skilled and innovative Lead Data Scientist to spearhead their artificial intelligence and machine learning initiatives in Cape Town. This critical role involves leading a team of data scientists and engineers to develop and deploy sophisticated predictive models and AI-driven solutions. You will play a key role in shaping the company's data strategy, identifying new opportunities for leveraging data, and driving impactful business outcomes through advanced analytics. This fully remote position offers the chance to work with a world‑class team from anywhere within South Africa, focusing on innovation and scientific rigor.

Key Responsibilities

• Lead the design, development, and implementation of advanced machine learning models and AI solutions to address complex business problems.
• Manage and mentor a team of data scientists, providing technical guidance and fostering a culture of continuous learning and innovation.
• Collaborate with stakeholders across departments to identify data-driven opportunities and translate business requirements into analytical projects.
• Develop and maintain data pipelines, ensuring data quality, integrity, and accessibility for modeling purposes.
• Stay abreast of the latest advancements in AI, ML, and data science, evaluating and incorporating new technologies and methodologies.
• Present complex findings and recommendations to technical and non-technical audiences effectively.

Requirements

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of experience in data science or machine learning, with at least 2 years in a leadership role.
• Proven track record of successfully developing and deploying machine learning models in production environments.
• Expertise in programming languages such as Python or R, and experience with relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of statistical modeling, data mining, and machine learning algorithms.
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms.

Benefits

• Highly competitive salary and annual bonus structure.
• Comprehensive medical, disability, and life insurance coverage.
• Generous stock options or equity participation.
• Significant budget for professional development, training, and conference attendance.
• Fully remote work environment with flexible hours.