Data Scientist (Kuala Lumpur)

Malaysia·Wp Kuala Lumpurmid

Data ScientistData

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Overview

Responsibilities Analyse large and complex datasets to identify trends, patterns, correlations and business opportunities.

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Data ScientistData

Responsibilities

~1 min read

→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

~1 min read

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.