Data Scientist (Senior)

ATS Client; Pretoria; On-site; ZAR 900,000 - 1,400,000; Full time

Job summary

ATS Client in Pretoria, South Africa, is seeking a Senior Data Scientist to translate business problems into data-driven AI solutions and collaborate with data engineering, AI platform, and observability teams.

You will design, build, and maintain data pipelines, develop ML models, evaluate them, and produce dashboards and reports for stakeholders.

Qualifications

• Proficiency in data analysis, ML, and ETL processes.

Responsibilities

• Translate business problems into data-driven and AI-enabled solutions.

Skills

Data analysis

EDA

Machine learning

Python

SQL

Data engineering

Spark

Dashboards

Stakeholder comms

Git

Tools

Excel

PowerBI

AWS

Quicksight

Kafka

Job description

Job Description

The Senior Data Scientist will be responsible for translating business problems into data-driven and AI-enabled solutions. The role requires strong expertise in data analysis, machine learning, data engineering, and stakeholder engagement, while working closely with data engineering, AI platform, and observability teams.

Key Responsibilities

• Translate business problems into data-driven and AI-enabled solutions
• Perform exploratory data analysis to uncover patterns, issues, and opportunities
• Design, build, and maintain data pipelines to support analytics and modelling use cases
• Develop, train, evaluate, and iterate on machine learning and AI models
• Apply appropriate model evaluation techniques and define success metrics
• Support operational data workflows and resolve day-to-day data processing issues when required
• Produce clear dashboards, reports, and visualisations for stakeholders
• Communicate insights, model behaviour, and recommendations to both technical and business audiences
• Collaborate closely with data engineering, AI platform, and observability teams to productionise solutions
• Contribute to best practices around data quality, governance, and responsible use of AI

Requirements

Essential Skills

• Excel, SQL, PowerBI, AWS and Quicksight
• Data analysis, exploration, and feature engineering (EDA)
• Strong applied statistics and machine‑learning foundations
• Python-based data science and ML stack (e.g. pandas, NumPy, scikit-learn, PyTorch / TensorFlow)
• Data engineering skills: ETL design, batch and streaming data processing
• Experience with distributed data systems (e.g. Kafka, Spark or equivalent)
• SQL and structured / semi‑structured data querying
• Experiment design, model evaluation, and validation techniques
• Dashboarding, reporting, and data visualisation
• Business problem translation and requirements understanding
• Version control and collaborative development (Git)

Advantageous Skills

• MLOps practices (model packaging, deployment pipelines, monitoring awareness)
• Data governance principles (data quality, lineage, ownership, compliance awareness)
• Model evaluation, performance tracking, and drift detection concepts
• Cloud-based data and ML environments (Azure / AWS)
• Generative AI and LLM-based solution experience
• AI agent or advanced prompting familiarity
• Experience collaborating with observability and platform engineering teams
• Domain-specific knowledge aligned to business use cases