The Role
Analyze complex datasets, develop and optimize statistical and machine learning models, and create AI solutions for business challenges. Clean and validate data, evaluate model performance, and collaborate with engineering, IT, and business stakeholders on deployment and improvement. Communicate analytical findings through reports, visualizations, and presentations while translating technical results into actionable recommendations. The role also requires staying current with data science, machine learning, generative AI, and responsible data practices.
Summary Generated by Built In
Responsibilities
- Analyse large and complex datasets to identify trends, patterns, correlations and business opportunities. Translate analytical findings into actionable insights and recommendations to support business decision-making.
- Develop, evaluate and optimise statistical models and machine learning algorithms for forecasting, classification, prediction, segmentation and anomaly detection based on business requirements.
- Explore and develop appropriate AI and advanced analytics solutions, including generative AI applications where relevant, to address business challenges, improve productivity and enhance organisational capabilities.
- Extract, clean, transform and validate data from multiple sources using appropriate tools and programming techniques. Ensure data quality, consistency and suitability for analysis and model development.
- Evaluate model accuracy, reliability and business relevance. Collaborate with data engineering, IT and relevant stakeholders to support solution deployment, performance monitoring and continuous improvement.
- Work with business stakeholders to understand requirements, define analytical approaches and communicate findings through reports, visualisations and presentations. Translate complex technical concepts into clear business recommendations.
- Keep abreast of developments in data science, machine learning and AI. Identify opportunities to improve analytical methodologies, adopt relevant technologies and promote responsible, secure and effective use of data-driven solutions.
Requirements
- Bachelor's Degree in Data Science, Statistics, Computer Science, Mathematics, Artificial Intelligence or a related quantitative discipline from a recognised institution.
- Minimum 2 years of relevant experience in data science, data analytics, statistical modelling or machine learning.
- Proficient in Python and SQL, with a good understanding of statistical methods, data manipulation, machine learning algorithms and model evaluation. Experience with data visualisation tools, cloud-based analytics platforms or machine learning deployment practices will be an advantage.
- Strong analytical thinking, problem-solving and communication skills, with the ability to translate business problems into analytical solutions, manage multiple priorities and collaborate effectively with technical and non-technical stakeholders.
Skills Required
- Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Artificial Intelligence, or a related quantitative discipline
- Minimum 2 years of relevant experience in data science, data analytics, statistical modelling, or machine learning
- Proficiency in Python and SQL
- Understanding of statistical methods, data manipulation, machine learning algorithms, and model evaluation
- Experience with data visualization tools, cloud-based analytics platforms, or machine learning deployment practices
- Strong analytical thinking, problem-solving, and communication skills
- Ability to translate business problems into analytical solutions, manage multiple priorities, and collaborate with technical and non-technical stakeholders
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The Company
What We Do
Edgenta Mediserve Sdn Bhd provides comprehensive hospital support services (HSS) to government hospitals and healthcare institutions in Malaysia. Its core business involves the provision of clinical waste management, cleansing services, linen and laundry, and specialized facilities and biomedical engineering maintenance, aimed at ensuring safe and efficient operational management of healthcare facilities.







