Senior Data Scientist - Financial Markets

Placements24; Gqeberha; Hybrid; ZAR 2,316,000 - 3,639,000; Full time

Benefits offered by this job

Stock options

Fully remote

Flexible hours

Continued learning

Job summary

Placements24 is seeking a Senior Data Scientist for a remote fintech team specializing in financial markets. You will craft predictive models, analyze large market datasets, and contribute to algorithmic trading and risk management initiatives.

Ideal candidates hold a PhD or Master's in a quantitative field with 5+ years in finance-related data science, strong Python or R skills, and experience with Spark/Hadoop for big data. This role offers stock options and flexible hours.

Qualifications

• PhD or Master's degree in Data Science, Statistics, CS, Mathematics, or related quantitative field.
• 5+ years hands-on Data Scientist experience with a focus on financial markets or quantitative finance.
• Strong programming in Python or R with ML libraries (Scikit-learn, TensorFlow, PyTorch).
• Experience with big data technologies (Spark, Hadoop) and databases.
• Deep understanding of financial instruments and market dynamics.

Responsibilities

• Design, develop, and implement advanced statistical and ML models for financial forecasting and risk assessment.
• Analyze large, complex financial datasets to identify patterns, trends, and actionable insights.
• Build and validate predictive models for trading strategies, portfolio optimization, and fraud detection.
• Collaborate with engineering to deploy models into production and monitor performance.
• Communicate complex findings to technical and non-technical stakeholders.
• Stay current with research in data science, ML, and quantitative finance.

Skills

Python

R

Quantitative analysis

Statistical modeling

Data visualization

Education

PhD or Master's in a quantitative field

Tools

Scikit-learn

TensorFlow

PyTorch

Spark

Hadoop

Job description

About the Role

Our client, a forward-thinking financial technology firm operating remotely, is seeking an exceptional Senior Data Scientist with expertise in financial markets . This role is central to leveraging vast datasets to uncover predictive insights, develop sophisticated quantitative models, and enhance trading strategies. You will collaborate with quants, traders, and engineers to drive innovation in algorithmic trading, risk management, and market analysis. The position offers a unique opportunity to work with cutting-edge technologies and contribute to developing next-generation financial solutions from anywhere, fostering a truly remote-first culture.

Key Responsibilities

• Design, develop, and implement advanced statistical and machine learning models for financial forecasting and risk assessment.
• Analyze large, complex datasets from financial markets to identify patterns, trends, and actionable insights.
• Build and validate predictive models for trading strategies, portfolio optimization, and fraud detection.
• Collaborate with engineering teams to deploy models into production environments and monitor their performance.
• Communicate complex analytical findings and model methodologies to both technical and non-technical stakeholders.
• Stay current with the latest research in data science, machine learning, and quantitative finance.

Requirements

• PhD or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• 5+ years of hands-on experience as a Data Scientist, with a strong focus on financial markets or quantitative finance.
• Proficiency in programming languages such as Python or R, and expertise in relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Experience with big data technologies (e.g., Spark, Hadoop) and database management.
• Strong understanding of financial instruments, market dynamics, and econometric modeling techniques.

Benefits

• Highly competitive salary and significant bonus potential tied to model performance.
• Fully remote working environment with flexible hours.
• Generous stock options and long-term incentive plans.
• Access to state-of-the-art computational resources and datasets.
• Continuous learning opportunities and support for attending industry conferences.