Editorial summary

The company is seeking an experienced Senior Data Scientist / Machine Learning Engineer for a permanent position with a salary of 6,500. The role involves analyzing data, developing and implementing machine learning models, and presenting insights to stakeholders to solve complex business problems. Candidates are expected to have expertise in data analysis, model development, and delivering analytics solutions. The position offers an opportunity to contribute to enhancing the company's analytics products and services.

This summary is AI-generated and may contain inaccuracies. Please refer to the full job description below.

Job description

[This job id 26489 first appeared in Job-Q.com on 21 Aug 2026]

We are seeking an experienced Senior Data Scientist / Machine Learning Engineer to join our dynamic team. As a Senior Data Scientist / Machine Learning Engineer, you will play a key role in analyzing and presenting data, developing and implementing machine learning models and algorithms to solve complex business problems. Your expertise will contribute to enhancing the delivery service of analytics solutions and products to our customers.

Job Responsibilities:

• 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, hyper parameter 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.

Job Requirements:

• 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

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