Senior Data Scientist, FinTech — Hybrid/Remote

Placements24; Stellenbosch; Hybrid; ZAR 900,000 - 1,600,000; Full time

Benefits offered by this job

Hybrid work model

Professional development opportunities

Medical/retirement benefits

Office in Stellenbosch

Job summary

Placements24 in Stellenbosch, Western Cape, seeks a Senior Data Scientist to join its analytics division in a hybrid role with remote days. You will develop predictive models, extract insights from large datasets, and drive data-informed decisions in finance.

The ideal candidate has a Master's or PhD in a quantitative field, 5+ years in data science, expertise in ML algorithms, Python or R, SQL, and experience with Spark/Hadoop.

Qualifications

• Master's or Ph.D. in a quantitative field (CS/Stats/Data Science).
• Minimum 5 years in data science or related analytics roles with financial focus.
• Strong proficiency in ML algorithms and statistical modeling.
• Proficient in Python or R and data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
• Solid SQL experience and handling large datasets; Spark/Hadoop a plus.

Responsibilities

• Design, develop, and deploy ML models for fraud detection, credit scoring, segmentation, and more.
• Analyze large datasets to identify trends and correlations for finance and customers.
• Develop and implement A/B testing to evaluate models and strategies.
• Collaborate with product, engineering, and business stakeholders to translate requirements into analytical solutions.
• Communicate findings clearly to technical and non-technical audiences; mentor junior data scientists.

Skills

Python

R

SQL

Machine learning

Data analysis

Communication

Hybrid teamwork

Education

Master's or PhD in Computer Science/Statistics/Data Science

Tools

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

Spark

Hadoop

Job description

Placements24 in Stellenbosch, Western Cape, seeks a Senior Data Scientist to join its analytics division in a hybrid role with remote days. You will develop predictive models, extract insights from large datasets, and drive data-informed decisions in finance.

The ideal candidate has a Master's or PhD in a quantitative field, 5+ years in data science, expertise in ML algorithms, Python or R, SQL, and experience with Spark/Hadoop.