Experienced Associate Data Engineer cum Scientist

Line of Service

Industry/Sector

Specialism

Management Level

Job Description & Summary

PwC Malaysia is seeking a versatile Data Scientist & Data Engineer to join our team. This hybrid role involves designing and maintaining robust data infrastructure while also developing advanced analytical and machine learning models. You will work closely with business stakeholders data scientists and engineers to deliver scalable data-driven solutions that address complex business challenges.

Key Responsibilities:

• Design develop and maintain scalable data pipelines and ETL/ELT workflows to ingest process and transform structured and unstructured data from multiple sources.

• Build and optimize data architectures leveraging cloud platforms such as AWS Azure or GCP to support analytics and machine learning workloads.

• Collaborate with cross-functional teams to identify data requirements ensure data quality and implement data governance standards.

• Perform exploratory data analysis and apply statistical techniques to extract actionable insights supporting business decision-making.

• Develop validate and deploy machine learning and predictive models to solve various client business problems.

• Monitor model performance in production and implement continuous improvement processes.

• Automate routine data management and analytical tasks to enhance efficiency.

• Create dashboards and data visualization reports to communicate findings to technical and non-technical stakeholders effectively.

• Stay current with emerging technologies and best practices in data engineering data science and AI to drive innovation within projects.

• Bachelors or Masters degree in Computer Science Data Science Engineering Statistics Mathematics or related fields.

• Minimum 2 years of professional experience across data engineering data science or combined analytics roles.

• Strong programming skills in Python SQL and experience with data engineering tools and frameworks (e.g. Apache Hadoop Spark Kafka Airflow).

• Proficiency with machine learning libraries such as scikit-learn TensorFlow or PyTorch.

• Experience with cloud platforms (AWS Azure GCP) and their data ecosystem (e.g. Redshift Synapse BigQuery).

• Solid understanding of data warehousing data modeling and ETL best practices.

• Strong foundation in statistics data mining and algorithm development.

• Ability to work collaboratively in dynamic hybrid team environments.

• Excellent communication skills capable of translating complex analyses into business insights.

Education (if blank degree and/or field of study not specified)

Certifications (if blank certifications not specified)

Required Skills

Optional Skills

Desired Languages (If blank desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship

Government Clearance Required

Job Posting End Date