Remote Data Scientist, Financial Modeling & Forecasting

Placements24; Gqeberha; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Remote work

Health insurance

Retirement contributions

Learning & development

Paid time off

Job summary

Placements24 is seeking a Data Scientist specializing in Financial Modeling to join a forward-thinking fintech team. This fully remote role centers on building predictive models for valuation, risk, and strategic financial insights within banking and finance.

You'll work with Python or R, leveraging pandas, scikit-learn, TensorFlow, and PyTorch to analyze large datasets and deliver actionable results. Collaboration with finance, product, and engineering teams is essential.

Qualifications

• Master's or PhD in a quantitative field required.
• 5+ years of Data Scientist experience focused on financial modeling or analytics.
• Proficiency in Python or R with libraries for ML and time series.

Responsibilities

• Design, develop, and implement advanced statistical and ML models for financial forecasting and risk assessment.
• Analyze large datasets to extract actionable insights and patterns.
• Develop financial models for valuation, portfolio optimization, and predictive analytics.
• Collaborate with finance, product, and engineering to define data requirements.
• Communicate findings with clear visualizations and reports.

Skills

Python

R

SQL

Time series analysis

Machine Learning

Data Visualization

Education

Master's or PhD in Data Science, Statistics, Mathematics, CS, Economics

Tools

pandas

scikit-learn

TensorFlow

PyTorch

Spark

Job description

Placements24 is seeking a Data Scientist specializing in Financial Modeling to join a forward-thinking fintech team. This fully remote role centers on building predictive models for valuation, risk, and strategic financial insights within banking and finance.

You'll work with Python or R, leveraging pandas, scikit-learn, TensorFlow, and PyTorch to analyze large datasets and deliver actionable results. Collaboration with finance, product, and engineering teams is essential.