[KYDP 2025 - Cohort 5] Junior Data Engineer

Intellista Consulting; Selangor; On-site; MYR 100,000 - 150,000; Full time

Job summary

A consulting firm in Selangor is seeking a Junior Data Engineer for the KYDP 2025 - Cohort 5 program. This role involves supporting the development of data-driven and AI-powered solutions, including responsibilities like dataset preparation, model testing, and data analysis. Candidates should have experience in data cleaning and visualization. The program runs from 1 October to 31 December, offering hands-on learning and development in data analytics and machine learning.

Qualifications

• Experience with data cleaning and preparation techniques.
• Familiarity with machine learning concepts and model development.
• Ability to analyze datasets to identify trends and patterns.

Responsibilities

• Collect and prepare datasets for analysis.
• Develop and test machine learning models with guidance.
• Analyze data and present findings effectively.
• Assist in deploying models into production environments.

Skills

Data cleaning

Machine learning

Data visualization

Data analysis

Job description

[KYDP 2025 - Cohort 5] Junior Data Engineer

Open To: Data Analytics, Prompt Engineering & Machine Learning

OJT Period:

[Cohort 5] - 1 October to 31 December

As a Data & AI Specialist, you will support the development, deployment, and maintenance of data-driven and AI-powered solutions that help drive business insights and automation. Your role includes working with structured and unstructured data, assisting in model development, and collaborating with teams to implement machine learning and data analytics pipelines. Some examples of your responsibilities include (but are not limited to) the following:

• Collecting, cleaning, and preparing datasets for analysis and model training
• Supporting the development and testing of machine learning models under the guidance of senior data scientists or AI engineers
• Analyzing data to uncover trends and patterns, and presenting findings in a clear, actionable manner
• Assisting in the deployment of AI models and data pipelines into production environments
• Documenting processes, methodologies, and results to ensure knowledge transfer and reproducibility
• Using data visualization tools to communicate insights and performance of models

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