Senior Data Scientist — Hybrid (Sandton) | ML, Fraud & Risk

Placements24; Sandton; Hybrid; ZAR 1,100,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Performance bonuses

Health benefits

Hybrid work model

Professional development

Job summary

Placements24 seeks a Senior Data Scientist in Sandton, Gauteng, offering a hybrid work setup. You will lead advanced ML initiatives, build predictive models, and work with cross-functional teams to embed data-driven decisions.

The role emphasizes fraud detection, segmentation, risk modeling, and scalable data pipelines. Requires a PhD or Master’s in a quantitative field and 5+ years of experience in data science, with strong Python/R, ML libraries, SQL and cloud skills.

Qualifications

• Master's or PhD in a quantitative field such as CS, stats, or math.
• 5+ years in data science, ML, or related roles, preferably in fintech/tech.
• Proficient in Python or R and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Strong SQL and big data tech experience (Spark, Hadoop).
• Excellent modeling, visualization, and communication skills.

Responsibilities

• Design, develop and deploy ML models to solve business problems.
• Analyze large datasets using statistical methods and data mining.
• Extract and present insights to technical and non-technical stakeholders.
• Collaborate with engineering/product teams to productionize solutions.
• Develop and maintain data pipelines, ensure data quality.
• Mentor junior data scientists and contribute to team growth.
• Stay updated on advances in data science and AI technologies.
• Contribute to data strategy and roadmap overall.

Skills

Python

R

TensorFlow

PyTorch

Scikit-learn

SQL

Spark

Hadoop

Data visualization

Communication

Education

Master's or PhD in CS/Statistics/Math/Data Science

5+ years in data science/ML

Tools

AWS

Azure

GCP

ML pipelines

Git

Job description

Placements24 seeks a Senior Data Scientist in Sandton, Gauteng, offering a hybrid work setup. You will lead advanced ML initiatives, build predictive models, and work with cross-functional teams to embed data-driven decisions.

The role emphasizes fraud detection, segmentation, risk modeling, and scalable data pipelines. Requires a PhD or Master’s in a quantitative field and 5+ years of experience in data science, with strong Python/R, ML libraries, SQL and cloud skills.