Enterprise Data Scientist /Analyst

We are looking for a skilled Data Scientist/ Data Analytics Engineer to join our consultancy client. They are looking for an experienced Enterprise Data Modeller to work on their clients data infrastructures and support AI and machine learning initiatives across various cloud platforms, including AWS and GCP. In this role, you will be integral to developing data pipelines and analytics solutions that directly impact business performance, while collaborating with cross-functional teams in a hybrid work setup of 2 days on site. Johannesburg or Cape Town based.

* Proficient in AWS services such as Redshift, S3, and Lambda, as well as GCP analytics tools
* Solid experience with data warehouse design and implementation
* Expertise in programming languages, preferably Python or SQL
* Familiarity with machine learning algorithms and their practical applications
* Understanding of data governance and compliance regulations

Key Responsibilities
Data Modelling & Architecture

* Design conceptual, logical and physical enterprise data models.
* Model complex business domains and large-scale datasets.
* Design schemas for transactional, analytical and AI workloads.
* Develop enterprise information models that enable reporting analytics and
machine-learning.
* Optimise enterprise data models for scalability, maintainability and performance.
Data Engineering
* Design and develop scalable ETL/ELT pipelines.
* Build reliable data ingestion pipelines for structured, semi-structured and
streaming data.
* Develop modern, cloud-based data platforms.
* Optimise data transformation, orchestration and storage.
* Support batch and real-time processing requirements.
* Ensure high levels of data quality and operational reliability.
Data Science & Machine Learning
* Develop statistical and machine learning models to solve business problems.
* Apply regression, classification, clustering, forecasting, anomaly detection and
optimisation techniques.
* Engineer features for production machine learning workloads.
* Evaluate, monitor and improve model performance.

Production Deployment
* Deploy machine learning solutions into production environments.
* Support model lifecycle management and monitoring.
* Work within established CI/CD deployment pipelines.
* Apply software engineering best practices to data and AI solutions.
* Build production APIs and inference services supporting AI and analytics
workloads.

Cloud-native Data Platforms
* Build and deploy data and AI solutions on Google Cloud Platform (preferred) or
AWS.
* Develop cloud-native data solutions using managed cloud services.
* Use Docker and modern software engineering practices to support deployments.

Technical Competencies
Programming
* Python (Expert)
* SQL (Expert)
* Bash/Shell
* Java or C/C++ advantageous

Enterprise Data Modelling
* Conceptual Data Modelling
* Logical Data Modelling
* Physical Data Modelling
* Enterprise Information Architecture
* Data Governance
* Data Lineage
* Metadata Management
* Data Quality
* Data Warehousing
* Dimensional Modelling

Data Engineering
* ETL/ELT
* Apache Kafka
* Airflow
* Pub/Sub
* BigQuery
* PostgreSQL
* Iceberg
* Parquet
* Streaming Data
* Data Warehousing

Machine Learning & Data Science
* Scikit-learn
* PyTorch
* XGBoost
* MLflow
* Vertex AI
* TensorFlow (advantageous)
* Statistical Modelling
* Time-series Forecasting
* Optimisation
* Feature Engineering

Cloud Technologies
* Google Cloud Platform (preferred)
* AWS
* Docker
* Git
* CI/CD Pipelines

Generative AI (Highly Desirable)
* Retrieval-Augmented Generation (RAG) Architectures
* LangChain / LangGraph
* Weaviate
* Model Context Protocol (MCP)
* LLM Evaluation

Essential Requirements
Intermediate

* Bachelor's degree or advanced degree in Computer Science, Data Science,
Statistics, Mathematics, Engineering or a related quantitative discipline.
* 4-6 years' experience in Data Engineering, Data Science or Machine
Learning Engineering.
* Demonstrated experience designing enterprise data models.
* Strong Python and SQL development skills.
* Experience building cloud-native data platforms.
* Experience deploying data or machine learning solutions into production.
* Experience working with Google Cloud Platform (preferred) or AWS.

Senior
* Bachelor's degree or advanced degree in Computer Science, Data Science,
Statistics, Mathematics, Engineering or a related quantitative discipline.
* Extensive experience designing enterprise data models for complex business
domains.
* Expert Python and SQL.
* Demonstrated ability to design enterprise data models for complex business
domains.
* Proven experience leading technical solution design.
* Experience mentoring engineers and contributing to architecture decisions.
* Experience working with Google Cloud Platform (preferred) or AWS.