Senior Data Scientist - Financial Modeling

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

Benefits offered by this job

Competitive salary

Bonuses

Health insurance

Retirement plans

Learning & development

Hybrid work model

Relocation assistance may be available

Paid time off and holidays

Wellness programs

Leadership growth potential

Job summary

Placements24 in Polokwane, Limpopo seeks a Senior Data Scientist specializing in Financial Modeling. You will design ML models for forecasting and risk, transform large data sources, and collaborate with analysts, engineers and product teams to implement production-ready solutions.

The role emphasizes model validation, stakeholder collaboration, and staying current with data-science innovations. Hybrid work setup with opportunities for leadership and growth in a fintech environment.

Qualifications

• Master’s or PhD in a quantitative field is required.
• At least 5 years of professional data science experience with financial modeling.
• Proficiency in Python or R and ML libraries (pandas, scikit-learn, TensorFlow, PyTorch).
• Strong SQL and database management experience.
• Experience deploying ML models in production environments.

Responsibilities

• Design, develop, and implement advanced statistical and machine learning models for financial forecasting, risk assessment, fraud detection, and customer behavior analysis.
• Extract, clean, and transform large datasets from various sources to prepare them for modeling.
• Perform rigorous model validation, performance testing, and back-testing to ensure accuracy and reliability.
• Collaborate with business stakeholders to understand their analytical needs and translate them into data science solutions.
• Develop and deploy predictive models into production environments, working closely with MLOps teams.
• Communicate complex findings and model results clearly and effectively to both technical and non-technical audiences.
• Stay abreast of the latest advancements in data science, machine learning, and financial modeling techniques.
• Mentor junior data scientists and contribute to the team's technical growth and best practices.
• Contribute to the development of data infrastructure and analytical tools.

Skills

Statistical analysis

Machine learning

Financial concepts

Data modeling

Problem solving

Education

Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Physics, Financial Engineering, or related quantitative field

Tools

Python

R

SQL

pandas

scikit-learn

TensorFlow

PyTorch

Spark

Hadoop

Job description

About the Role Our client, a leading innovator in financial technology, is seeking an exceptional Senior Data Scientist specializing in Financial Modeling to join their team in Polokwane, Limpopo . This role is pivotal in leveraging advanced data analytics and machine learning techniques to build sophisticated financial models that drive critical business decisions, optimize risk management, and enhance predictive capabilities. The ideal candidate will possess a strong blend of statistical expertise, programming proficiency, and a deep understanding of financial concepts. You will collaborate with cross-functional teams, including quantitative analysts, engineers, and product managers, to translate complex data into actionable insights. This position offers a stimulating work environment where you can apply cutting-edge methodologies to solve challenging problems in the financial sector. We are looking for a passionate data scientist who can lead complex projects and mentor junior team members, contributing significantly to the company's analytical prowess and strategic direction.

Key Responsibilities

• Design, develop, and implement advanced statistical and machine learning models for financial forecasting, risk assessment, fraud detection, and customer behavior analysis.
• Extract, clean, and transform large datasets from various sources to prepare them for modeling.
• Perform rigorous model validation, performance testing, and back-testing to ensure accuracy and reliability.
• Collaborate with business stakeholders to understand their analytical needs and translate them into data science solutions.
• Develop and deploy predictive models into production environments, working closely with MLOps teams.
• Communicate complex findings and model results clearly and effectively to both technical and non-technical audiences.
• Stay abreast of the latest advancements in data science, machine learning, and financial modeling techniques.
• Mentor junior data scientists and contribute to the team's technical growth and best practices.
• Contribute to the development of data infrastructure and analytical tools.

Requirements

• Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Physics, Financial Engineering, or a related quantitative field.
• Minimum of 5 years of professional experience as a Data Scientist, with a strong focus on financial modeling and analysis.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
• Strong experience with SQL and database management.
• Demonstrated experience in building and deploying machine learning models in a production environment.
• Solid understanding of financial markets, instruments, and risk management principles.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Ability to work effectively in a hybrid work setting in Polokwane .

Benefits

• A highly competitive salary package of up to ZAR per annum.
• Generous performance-based bonuses and potential for stock options.
• Comprehensive health insurance and retirement savings plans.
• Opportunities for continuous learning, professional development, and attending industry conferences.
• A dynamic and innovative work environment with access to cutting-edge technology.
• Hybrid work model providing flexibility.
• Relocation assistance may be available.
• Paid time off and public holidays.
• Employee wellness programs and initiatives.
• Collaborative team atmosphere and potential for leadership growth.