Senior Data Scientist

Pepkor Payments & Lending; Cape Town; On-site; ZAR 400,000 - 500,000; Full time

Job summary

A leading financial services company located in Cape Town is seeking a Data Scientist to enhance business decisions through data solutions. Responsibilities include gathering information, developing machine learning models, collaborating on strategy deployment, and monitoring performance. Ideal candidates should have strong skills in data engineering, SQL, Python, and analytics.

Qualifications

• Experience in data engineering and management disciplines.
• Strong understanding of predictive, prescriptive, and cognitive analytics.
• Ability to monitor model performance and campaign success.

Responsibilities

• Identify opportunities to solve problems using data science solutions.
• Develop machine learning models for marketing and credit risk assessment.
• Collaborate with teams to deploy models and strategies.

Skills

Data science solutions

SQL

Python

Machine learning models

Job description

The Data Scientist is responsible for creating business value by applying data engineering and data management disciplines to build data solutions that enable data-driven decision support, in order to optimize business decisions and processes.

Key Responsibilities

1. Information Gathering and Solution Design

• Identify opportunities in the business to solve problems using data science solutions.
• Assess the viability of business requests and ideas in predictive, prescriptive, and cognitive analytics.
• Support project definition focusing on value creation.
• Conceptualize solutions to generate maximum value.

Data Processing and Manipulation

• Find, clean, and structure data in SQL and Python environments.
• Support marketing with data requirements and performance feature creation.
• Design and build feature stores for model development and deployment.

Model Development and Validation

• Develop machine learning models for marketing and credit risk assessment.
• Optimize models for accuracy, interpretability, and performance.
• Document and present models to stakeholders.

Strategy Development

• Develop decision strategies utilizing models to improve decision-making.
• Design champion/challenger strategies to evaluate model effectiveness and quantify benefits.

Deployment

• Collaborate with ML engineers, IT, and credit risk teams to deploy models and strategies.

Monitoring and Maintenance

• Monitor and improve model and strategy performance.
• Monitor campaign performance and identify data science techniques for improvement and automation.

Personal and Functional Leadership

• Own your work, deliver high-quality results on time.
• Proactively seek opportunities to improve data and processes.
• Continuously develop skills and knowledge, and mentor team members.