Senior Data Scientist

Jobstreet Malaysia; Kuala Lumpur; On-site; MYR 60,000 - 90,000; Full time

Job summary

A leading recruitment platform is seeking a Senior Data Scientist to lead advanced analytics and machine learning initiatives. The ideal candidate will have 3–5 years of experience, strong skills in SQL and PySpark, and hands-on experience with Databricks. Responsibilities include building ETL pipelines, managing data workflows in Azure, and supporting data scientists with feature engineering and model development. This is an opportunity to make a significant business impact in a collaborative environment.

Qualifications

• 3–5 years of experience in data engineering or data science roles.
• Good understanding of machine learning concepts and ML pipelines.
• Ability to work with cloud services (Azure, AWS, GCP).

Responsibilities

• Build, maintain, and optimise ETL/ELT pipelines using SQL, PySpark, and Databricks.
• Manage and orchestrate data workflows within Azure Databricks.
• Support data scientists in feature engineering and model development.

Skills

Data engineering experience

Proficiency in SQL

Strong in PySpark

Hands-on experience with Databricks

Business acumen

Tools

Databricks

Azure Data Factory

ADLS

Job description

We are seeking a Senior Data Scientist to lead advanced analytics and machine learning initiatives while strengthening the cloud-based data platform. This role requires strong hands‑on experience, end‑to‑end ownership, and the ability to translate data insights into business impact.

Key Responsibilities

• Build, maintain, and optimise ETL/ELT pipelines using SQL, PySpark, and Databricks
• Design and enhance Delta Lake / Lakehouse architectures
• Manage and orchestrate data workflows within Azure Databricks
• Support data scientists in feature engineering, model development, and experimentation
• Ensure data quality, governance, security, and performance across data platforms

Key Requirements

• 3–5 years of experience in data engineering / data science roles
• Strong proficiency in SQL, PySpark, Python, and cloud‑based data processing
• Hands‑on experience with Databricks (notebooks, MLflow, orchestration)
• Experience with Azure Data Factory, ADLS, or similar cloud services
• Good understanding of machine learning concepts and ML pipelines

Primary Skill Set

• Advanced Modelling & ML Expertise – Experience in building complex models (ML, deep learning, NLP, forecasting) and applying advanced statistical techniques
• Programming & Data Engineering – Strong in Python/R/SQL, Spark, and exposure to Hadoop; experience with Azure / AWS / GCP
• End‑to‑End Ownership – Able to scope, design, build, deploy, and monitor data products independently
• Business Acumen – Strong ability to understand business needs and translate them into data‑driven solutions
• Collaboration & Mentorship – Works closely with cross‑functional teams and mentors junior data scientists