Senior Data Scientist

Ernst & Young Advisory Services Sdn Bhd; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

A global consultancy in Kuala Lumpur is seeking a Technical Lead – AI and Data. The role requires leading complex data science, machine learning, and data engineering projects with over 5 years of experience. Candidates should have a strong understanding of machine learning techniques and be proficient in SQL. This position offers flexibility and involves managing a team of data professionals while ensuring alignment with business objectives.

Qualifications

• 5+ years of hands-on experience in relevant roles.
• Proven track record in designing and delivering AI solutions.
• Strong understanding of machine learning techniques.
• Familiar with data governance and ML Ops principles.

Responsibilities

• Lead solutioning for AI and data projects.
• Ensure technical solutions align with business goals.
• Manage and groom a team of Data scientists and Engineers.
• Present technical designs to stakeholders.

Skills

data science

machine learning

data engineering

advanced analytics

SQL

cloud-native architecture

Big Data technologies

Education

Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Engineering, or a related field

Tools

Apache Spark

Kafka

Airflow

Job description

The opportunity

EY AI & Data is the data and advanced analytics capability within EY Asia‑Pacific, with over 500 specialist employees working across multiple industry sectors. We implement information‑driven strategies and systems that help grow, optimise and protect client organisations. We go beyond strategy and provide end‑to‑end implementation of real‑life data environments and have some of the best architects, project managers, business analysts, data scientists, big data engineers, developers and consultants in the region.

We are looking for a Technical Lead – AI and Data within the AI & Data team in our Malaysia office to lead solutioning for complex AI, data science and data engineering transformation projects. This role is offered on a flexible full‑time basis.

Your key responsibilities

• Be a part of a culture that focuses on delivering excellence for our clients and work with an awesome team of people to work with and access to cutting edge technologies.
• Flexibility to work in the way that brings out the best in you and encourages you to do what you love, in an environment that supports you.
• Be involved in all aspects of the Project life cycle, including Strategy, Road‑Mapping, Architecture, Implementation and Development to gain maximum exposure.
• Ensure technical solutions align with business objectives and adhere to industry standards and best practices.
• Present technical designs, insights, and solution outcomes to both technical and non‑technical stakeholders.
• Manage and groom a team of Data scientists and Data Engineers, helping nurture and grow talent.

What we look for

• 5+ years of hands‑on experience in data science, GenAI, machine learning, data engineering, or advanced analytics roles.
• Proven track record in designing and delivering end‑to‑end AI and data solutions at scale.
• Experience in building Generative AI based RAG solutions or proof‑of‑concepts.
• Strong understanding of machine learning techniques including supervised/unsupervised learning, NLP, deep learning, and model deployment best practices.
• Experienced in working with large, complex datasets and data pipelines (ETL/ELT).
• Familiarity with data governance, data quality, and ML Ops principles.
• Proficient in SQL and experience with relational and NoSQL databases.
• Knowledge of Big Data technologies and cloud‑native architecture (e.g., Azure, AWS, GCP).
• Bachelor's or Master’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.

Ideally, you’ll also have

• Experience with NLP tools (e.g., spaCy, Hugging Face) and Large Language Models (LLMs)
• Familiarity with agile, DevOps, and CI/CD delivery practices.
• Knowledge of data engineering tools (e.g., Apache Spark, Kafka, Airflow).
• Hands‑on experience designing modern data platforms such as data lakes or lakehouses.
• Certifications in cloud platforms (AWS, Azure, GCP) are advantageous.