Johannesburg: Lead Data Scientist – Johannesburg – up to R1.2mil per annum posted by E-Merge

About the Role

E-Merge, a reputable bank with decades of experience in the financial services sector, is seeking an experienced Lead Data Scientist to design, develop, and deploy advanced AI and machine learning solutions across the organization. The ideal candidate will combine deep technical expertise with strong analytical and leadership skills to drive data-driven decision-making, work with unstructured and structured datasets, and deliver measurable business impact.

Key Responsibilities

• Lead the design, development, and deployment of ML and AI models (Linear, 3-Phased, Deep Learning) across business-critical processes.
• Work end-to-end on AI projects, including the six key AI processes: data collection, data preprocessing, feature engineering, model development, model evaluation, and deployment/monitoring.
• Conduct real-time data screening and analytics for structured and unstructured data (location data, images, voice notes, text).
• Develop and maintain dashboards using tools such as R Shiny, Dash, and other BI platforms to communicate insights effectively.
• Drive ML Ops practices, including Responsible AI monitoring, model retraining, and performance tracking.
• Collaborate with cross-functional teams to identify opportunities for data mining and AI-driven optimization of business processes.
• Ensure AI-based solutions are production-ready, documented, and measurable, showing evidence of successful deployment.
• Provide technical leadership and mentorship to junior data scientists and analysts.
• Manage data infrastructure and pipelines using Big Data frameworks (Hadoop, Spark, I-Spark, Spark-R), AWS, Kafka, and SAS Viya.

Requirements

• Master’s or PhD in Data Science, Statistics, Computer Science, Physics, or related field.
• Programming & Tools: Python, R, SQL, SAS Viya, Spark-R, I-Spark, TensorFlow/PyTorch.
• Big Data & Cloud: Hadoop ecosystem, AWS, Kafka, Confluence.
• Analytics & AI: Machine Learning, Deep Learning, AI-based solutions, model deployment, ML Ops.
• Data Handling: Experience working with structured and unstructured data (text, images, voice, geolocation).
• Visualization & Reporting: R Shiny, Dash, Power BI, and other dashboarding tools.
• Soft Skills: Strong analytical thinking, problem-solving, leadership, and collaboration skills.
• Experience: Proven track record of end-to-end AI/ML project delivery and evidence of successful model deployment.

Qualifications

No formal education or certifications mentioned in the original job description.