Data Science Lead Job Vacancy Financial Services

Position:
Data Science Lead

Company:
Standard Bank Group

Location:

Johannesburg, South Africa

Experience:

5+ years in data science, machine learning, and analytics

Education:

Bachelor’s degree in Computer Science, Statistics, or related field;
Master’s preferred

Employment Type:

Full-time

Industry: Financial Services

Department:
Data & Analytics

Salary: R900,000 – R1,300,000 per annum

Vacancies: 1

Standard Bank Group, headquartered in Johannesburg, is one of Africa’s largest financial institutions with a presence in over 20 countries. The bank is renowned for its commitment to innovation, sustainability, and inclusive growth, offering a wide range of banking, investment, and wealth management services. As a top employer in South Africa, Standard Bank fosters a collaborative culture that emphasizes continuous learning and purpose‑driven work, making it an attractive destination for ambitious professionals seeking career opportunities in South Africa.

The Data Science Lead will drive the creation and deployment of advanced machine learning models that enhance credit scoring, fraud detection, and customer segmentation across the bank’s retail and corporate divisions. Reporting to the Head of Data Strategy, you will partner with product, risk, and technology teams to turn complex data into strategic insights, directly influencing the bank’s digital transformation agenda.

• Lead end‑to‑end data science projects, from problem definition to model production and monitoring.
• Develop predictive models for credit risk, fraud detection, and customer segmentation.
• Collaborate with data engineers to ensure robust data pipelines and high‑quality data sources.
• Mentor junior data scientists and champion best practices in model governance.
• Present analytical findings to senior leadership, translating technical concepts into business recommendations.
• Evaluate emerging AI/ML technologies for potential banking applications.

• Proficiency in Python or R with experience in scikit‑learn, Tensor Flow, or PyTorch.
• Strong statistical modeling, hypothesis testing, and experimental design abilities.
• Hands‑on experience with big data platforms (Spark, Hadoop) and cloud services (AWS, Azure, or GCP).
• Excellent communication skills for non‑technical stakeholder engagement.
• Leadership experience managing multidisciplinary teams.
• Financial services domain knowledge is a plus.

A Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline is required. A Master’s or PhD in Data Science, Machine Learning, or a comparable field is highly preferred.

Minimum five years of professional experience in data science or advanced analytics, preferably within banking or financial services, with a proven record of delivering production‑grade machine learning solutions.

The compensation package ranges from R900,000 to R1,300,000 per annum, commensurate with experience, plus performance‑based bonuses and comprehensive benefits.

• Competitive health and medical insurance covering employees and dependents.
• Retirement savings plan with employer contributions.
• Generous paid leave, including annual, sick, and parental leave.
• Employee assistance program and wellness initiatives.
• Flexible working arrangements and remote‑work options.

• Access to internal and external AI/ML certification programs.
• Annual budget for conferences, workshops, and continuous education.
• Mentorship from senior data leaders and cross‑functional experts.
• Structured onboarding and ongoing skill‑development pathways.

Standard Bank offers a modern, inclusive workplace that values diversity of thought. Our Johannesburg office features open‑plan spaces, quiet zones, and state‑of‑the‑art technology to support innovative work. Employees benefit from supportive leadership that encourages autonomy and creativity.

Standard Bank Group is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, gender, age, disability, religion, or sexual orientation. Our hiring practices ensure fair consideration for every applicant.