Senior Data Scientist / Machine Learning Engineer
Summary
Build and deploy ML models to deliver AI-driven insights for mission-critical systems in defence, government, and commercial sectors using Python, TensorFlow/PyTorch, and cloud infrastructure.
- Data analysis and insights: Perform exploratory data analysis, generate insights, and present findings to stakeholders. Use statistical methods and visualization techniques to communicate complex concepts and patterns effectively.
- Develop and deploy machine learning models: Design, build, and optimize machine learning models and algorithms to solve specific business problems. Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models into production environments.
- Model training and evaluation: Train and fine-tune machine learning models using appropriate algorithms and techniques. Evaluate model performance and identify areas for improvement, employing techniques such as cross-validation, hyperparameter optimization, and ensemble methods.
- Model deployment and integration: Collaborate with software engineers and DevOps teams to deploy machine learning models into production environments. Implement APIs and integrate models with existing systems and applications to enable real-time decision-making.
- Performance monitoring and maintenance: Monitor model performance and address any issues or anomalies that arise. Continuously improve models by refining algorithms, optimizing code, and incorporating feedback from users and stakeholders.
- Stay up-to-date with the latest advancements: Keep abreast of the latest research and trends in machine learning and artificial intelligence. Evaluate and recommend new tools, libraries, and methodologies to enhance the efficiency and effectiveness of the machine learning workflow.
- Shall have at least three (3) years of implementation and deployment experience in machine learning and statistical data analysis on large datasets.
- Shall have experience in translating business questions into analytical problems and using statistical techniques to derive actional insights using statistical software (Python, R, SAS), database languages (SQL), visualization tools (Qlik Sense), and deep learning framework (TensorFlow, PyTorch).
- Shall have the following skillsets: Data Wrangling, Data Visualization, DBMS, SQL, Python
- Preferably have completed at least one (1) project using Scrum or equivalent Agile development framework.
- Experience in these products/tools would be advantageous: MS Access (Front-end), SharePoint (Back-end), Power BI (Visualisation), Kubernetes, Docker/Podman, Microservices Architecture, DevSecOps Methodology
- An environment where you will be working on cutting-edge technologies and architecture.
- Safe space where diverse perspectives are valued, and everyone's unique contributions are celebrated
- Meaningful work and projects that make a difference in people's lives.
- A fun, passionate and collaborative workplace.
- Competitive remuneration and comprehensive benefits.