Data Scientist II

Job Description

This role is for a hands‑on Data Scientist responsible for building and deploying machine learning solutions that drive business value. The position involves end‑to‑end work across data preparation, exploratory analysis, model development, experimentation, production deployment, and ongoing model monitoring. The ideal candidate should have strong Python and SQL skills, solid ML and statistical foundations, and experience delivering real‑world models. You will collaborate closely with cross‑functional teams, communicate insights to stakeholders, and contribute to both technical excellence and data governance, while mentoring junior team members.

Data Scientist / Machine Learning Engineer

Welcome to FNB, the home of the #changeables. We design for the shapeshifters and deliver products and services that make us incredibly proud of people that make it happen.

• 3+ years in Data Science / ML
• Strong Python & SQL, beneficial Spark
• Solid grounding in ML principles, software engineering and statistics
• Experience with model development, evaluation, and deployment
• Strong communicator, strong problem‑solver

• Master’s in Data Science / Computer Science
• BSc / Honours in Data Engineering, Computer Science, or similar

• Challenging work
• A culture of collaboration

• Collect, clean, and preprocess data from multiple sources, including databases, APIs, and external datasets, ensuring data quality, integrity, and consistency.
• Perform exploratory data analysis (EDA) to understand the structure, distribution, and relationships within datasets, using statistical methods and visualization tools to identify patterns and insights.
• Develop predictive models and machine learning algorithms to solve business problems, such as fraud as well as customer personalisation.
• Apply advanced statistical techniques, such as regression analysis, clustering, classification, and time series analysis, to extract actionable insights from data and make data‑driven decisions.
• Design and implement experiments and A/B tests to evaluate hypotheses, measure performance, and optimise processes, products, or marketing campaigns.
• Collaborate with cross‑functional teams, including data engineers, software developers, and business analysts, to deploy machine learning models and integrate them into production systems.
• Interpret and communicate findings, insights, and recommendations to stakeholders, including executives, managers, and business partners, using data visualization tools and storytelling techniques.
• Monitor and evaluate model performance, accuracy, and effectiveness over time, adjusting models and algorithms as needed to improve predictive power and business outcomes.
• Stay updated on advances in data science, machine learning, and AI technologies.
• Contribute to data governance and data management initiatives, ensuring compliance with privacy regulations, data security standards, and best practices for data handling and storage.
• Collaborate with business stakeholders to define project requirements, scope, and success criteria, aligning data science initiatives with business goals and objectives.
• Conduct ad‑hoc analyses and data mining exercises to answer specific business questions, explore new opportunities, and uncover hidden insights in data.
• Mentor and coach junior data scientists, providing guidance, support, and feedback on technical skills, analytical methods, and professional development.
• Demonstrate integrity, ethics, and professionalism in handling sensitive data and maintaining confidentiality, ensuring compliance with legal and ethical standards.

• Proven experience as a data scientist or in a similar role, with hands‑on experience in data analysis, machine learning, and statistical modelling.
• Proficiency in programming languages and tools used in data science, such as Python, R, SQL, and libraries/frameworks like Tensor Flow, PyTorch, scikit‑learn, and pandas.
• Strong analytical and problem‑solving skills, with the ability to formulate hypotheses, design experiments, and interpret results to derive actionable insights.
• Knowledge of statistical methods, machine…