Senior Data Scientist

• Design and develop high-quality, reusable features for business-critical ML models.
• Apply advanced machine learning techniques (e.g., supervised, unsupervised, deep learning) to solve complex business problems.
• Conduct data discovery and exploratory analysis to identify valuable features and patterns.
• Contribute to the feature store lifecycle, including documentation, versioning, and governance.
• Apply graph-based techniques to model relationships and extract features for downstream ML tasks.
• Monitor and continuously improve deployed models, ensuring performance, fairness, and ethical compliance.
• Implement design of experiments, hypothesis testing, and model validation strategies.
• Build and maintain scalable, production-grade data pipelines for feature computation and model training.
• Transform raw data into clean, structured, analytics-ready datasets using modern data engineering tools (e.g., dbt, Airflow, Spark).
• Engineer real-time and batch data workflows to support ML and analytics use cases.
• Collaborate with other data engineers and scientists to ensure seamless integration of features into model pipelines.
• Implement data quality checks, monitoring, and validation processes to ensure reliability and trust in analytical outputs.
• Optimize data workflows for performance, cost-efficiency, and maintainability across cloud and on-prem environments.
• Translate complex data narratives into actionable business insights.
• Work closely with business stakeholders to understand requirements and deliver data-driven solutions.
• Architect analytical systems that support business strategy, objectives, and values.
• Contribute to use case roadmaps and prioritization aligned with strategic goals.
• Stay abreast of developments in ML, analytics engineering, and data infrastructure to drive innovation.
• Mentor junior data scientists and contribute to quality assurance across the team.
• Collaborate cross-functionally with data science, engineering, BI, and business teams.
• Promote ethical AI practices and ensure models in production are aligned with responsible AI principles.
• Support Nedbank's culture-building and corporate responsibility initiatives.

• Matric / Grade 12 / National Senior Certificate
• Advanced Diplomas/National 1st Degrees

• BSC Computer Science, Engineering, Econometrics, Mathematical Statistics, Actuary Science or any STEM qualification
• Masters Degree Computer Science, Engineering, Econometrics, Mathematical Statistics, Actuary Science or any STEM qualification.

• Machine Learning and Data Engineering related

• 7 years' plus experience in a statistical and/or data science role.

• Data Science
• ML Engineering
• Data Warehousing
• Advanced analytics
• Marketing analytics
• Financial analytics
• Presentations skills
• Predictive analytics
• Data mining
• Strategy formulations

• Strong proficiency in Python (required), with experience in R, Scala, or SQL.
• Experience with distributed computing tools (e.g., Spark, Ray) and cloud platforms.
• Familiarity with graph databases (e.g., Neo4j, TigerGraph) and graph analytics.
• Deep understanding of the data science lifecycle and analytics engineering principles.
• Experience in the financial services domain, with knowledge of regulatory and business-specific data contexts.
• Excellent communication skills and ability to work in cross-functional teams.
• Exposure to feature store platforms, ML model deployment, and MLOps practices.

• Strong problem-solving skills
• Good communication skills
• Ability to work in teams
• Decision Making
• Innovation
• Continuous Improvement

Nedbank