Lead Data Scientist

Placements24; LegKraal Gate; Hybrid; ZAR 900,000 - 1,800,000; Full time

Benefits offered by this job

Executive salary bonus

Medical and retirement benefits

Hybrid work arrangement

Career growth opportunities

Job summary

Placements24 in Mahikeng seeks a seasoned Lead Data Scientist to spearhead data analytics initiatives, define data strategy, and drive data-driven decision-making across the organization.

You will mentor a team of data scientists and analysts, collaborate with departments to identify data opportunities, and ensure robust, scalable analytical solutions. A hybrid work arrangement is offered to support balance.

Qualifications

• Ph.D. or Master’s in Data Science, Statistics, Computer Science, or related quantitative field.
• 7+ years of experience in data science with leadership exposure.
• Expertise in statistical modeling, ML algorithms, and data mining techniques.
• Python or R and ML libraries (Scikit-learn, TensorFlow, PyTorch)
• Experience with big data tech (Spark, Hadoop) and databases.
• Strong analytical, problem-solving, and communication skills.

Responsibilities

• Lead the development and deployment of ML models and analytical solutions to address complex business problems.
• Define and execute the company's data science strategy and roadmap.
• Mentor and guide a team of data scientists and analysts, fostering innovation and technical excellence.
• Collaborate with stakeholders across departments to identify data needs and opportunities for analytics.
• Perform advanced statistical analysis, data mining, and predictive modeling using large datasets.
• Communicate complex findings and recommendations to both technical and non-technical audiences.

Skills

Data science leadership

Machine learning

Statistical modeling

Python

Big data

Communication

Education

Ph.D. in Data Science

Tools

Scikit-learn

TensorFlow

PyTorch

Spark

Job description

About the Role

Our client is seeking an accomplished Lead Data Scientist to spearhead their data analytics initiatives in Mahikeng. This leadership role involves defining data strategy, developing advanced predictive models, and driving data-driven decision‑making across the organization. You will mentor a team of data scientists and analysts, collaborate with various departments to identify opportunities for leveraging data, and ensure the implementation of robust, scalable analytical solutions. This is an exceptional opportunity for a seasoned professional to shape the future of data science within a growing company.

Key Responsibilities

• Lead the development and deployment of machine learning models and analytical solutions to address complex business problems.
• Define and execute the company's data science strategy and roadmap.
• Mentor and guide a team of data scientists and analysts, fostering a culture of innovation and technical excellence.
• Collaborate with stakeholders across departments to identify data needs and opportunities for analytics.
• Perform advanced statistical analysis, data mining, and predictive modeling using large datasets.
• Communicate complex findings and recommendations clearly to both technical and non‑technical audiences.

Requirements

• Ph.D. or Master's degree in Data Science, Statistics, Computer Science, or a related quantitative field.
• 7+ years of experience in data science, with demonstrated experience in leading projects and teams.
• Expertise in statistical modeling, machine learning algorithms, and data mining techniques.
• Proficiency in programming languages commonly used in data science (e.g., Python, R) and relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Experience with big data technologies (e.g., Spark, Hadoop) and database management.
• Strong analytical, problem‑solving, and communication skills.

Benefits

• Highly competitive executive-level salary and bonus structure.
• Comprehensive medical and retirement benefits.
• Significant opportunities for strategic impact and career growth.
• Hybrid work arrangement to support work-life balance.
• Access to advanced tools and resources for data analysis.
• A dynamic and collaborative work environment fostering continuous learning.