Senior Data Scientist
Senior Data Scientist
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1 Vacancy
Job Description
Requisition Details & Talent Acquisition Specialist
REQ 141722 - Keabetswe Modise
Closing Date: 06 September 2025
Job Family
Information Technology
Career Stream
Application Development
Leadership Pipeline
Manage Self Expert
Job Intro
Join an exciting fun data science team who are passionate about what they do and have fun while doing it. We work hard and play hard and we have an impact on our customers. We have many solutions in Production and we are always learning.
Job Purpose
Apply domain-specific expertise in machine learning data mining and information retrieval to architect and build highly specialized and advanced analytic engines and services pushing the boundaries of knowledge in the field and providing expert guidance to the enterprise.
Job Responsibilities
- 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 Nedbanks culture-building and corporate responsibility initiatives.
Essential Qualifications - NQF Level
- Matric / Grade 12 / National Senior Certificate
- Advanced Diplomas/National 1st Degrees
Preferred Qualification
- 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.
Preferred Certifications
- Machine Learning and Data Engineering related
Minimum Experience Level
- 7 years plus experience in a statistical and/or data science role.
Type of Exposure
- Data Science
- ML Engineering
- Data Warehousing
- Advanced analytics
- Marketing analytics
- Financial analytics
- Presentations skills
- Predictive analytics
- Data mining
- Strategy formulations
Technical / Professional Knowledge
- 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.
Behavioural Competencies
- Strong problem-solving skills
- Good communication skills
- Ability to work in teams
- Decision Making
- Innovation
- Continuous Improvement
Please contact the Nedbank Recruiting Team at
Required Experience:
Senior IC
Employment Type
Full Time
