Remote Lead Data Scientist – Banking & Finance

Placements24; Sandton; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Bonus potential

Health insurance

Retirement plan

Remote-friendly

Job summary

Placements24 is seeking a Lead Data Scientist for a remote role in South Africa. You will lead a team of data scientists, developing and deploying advanced ML models to drive insights, optimize financial products, and enhance customer experiences across the Banking & Finance sector.

The ideal candidate has a PhD or Master’s in a quantitative field, 7+ years in data science (3+ in leadership), strong Python/R skills, and a track record of production ML deployments.

Qualifications

• PhD or master's in a quantitative field.
• 7+ years in data science, with 3+ in leadership.
• Proven track record deploying ML models in production.
• Experience in Banking & Finance sector is a plus.

Responsibilities

• Lead a team of data scientists, providing guidance and oversight.
• Develop and deploy ML models for fraud detection, segmentation, credit scoring.
• Design experiments and A/B tests to measure impact.
• Clean, transform, and analyze large datasets from diverse sources.
• Collaborate with product, engineering, and business teams to deploy solutions.
• Communicate findings to technical and non-technical audiences.
• Ensure data governance, ethics, and privacy best practices.

Skills

Leadership

Machine learning

Data analysis

Education

PhD in Data Science or related

Tools

Python

R

scikit-learn

TensorFlow

PyTorch

SQL

Spark

Hadoop

Job description

Placements24 is seeking a Lead Data Scientist for a remote role in South Africa. You will lead a team of data scientists, developing and deploying advanced ML models to drive insights, optimize financial products, and enhance customer experiences across the Banking & Finance sector.

The ideal candidate has a PhD or Master’s in a quantitative field, 7+ years in data science (3+ in leadership), strong Python/R skills, and a track record of production ML deployments.