Senior Staff Data Scientist [up to 30k]

Randstad; Kuala Lumpur; Hybrid; MYR 120,000 - 150,000; Full time

Job summary

A leading recruitment firm in Kuala Lumpur is searching for a Senior Staff Data Scientist to lead technical vision and drive the development of a next-generation segmentation engine. This role involves mentoring a team, collaborating with product leadership, and developing scalable model solutions. Candidates should have over 8 years of experience in data science, proficiency in Python and PySpark, and a Bachelor’s degree in a related field. This hybrid position promises a strategic yet hands-on approach to data science.

Qualifications

• 8–12+ years of experience in data science with at least 3–4 years in a senior role.
• Expertise in unsupervised learning and ML models.
• Proficient in distributed data processing.

Responsibilities

• Lead and mentor a team of data scientists.
• Collaborate with leadership to define the roadmap.
• Design and build large-scale segmentation systems.

Skills

Python

SQL

R

PySpark

Machine Learning

Deep Learning

Data Visualization

AWS

Azure

GCP

Education

Bachelor's degree in Computer Science

Tools

Tableau

Databricks

Job description

About the Role

As a Senior Staff Data Scientist, you will lead the technical vision and roadmap for the company’s next-generation segmentation engine. You will drive architectural decisions, mentor senior data scientists, and ensure the delivery of scalable, high-impact models. This is a hybrid leadership role: highly strategic, but still deeply hands‑on in model development, experimentation, and solution design.

Responsibilities

• Lead, mentor, and upskill a team of data scientists and analysts; set best practices and standards in modelling, experimentation, and MLOps.
• Collaborate with product and engineering leadership to define the long‑term roadmap and ensure alignment with business goals.
• Design, architect, build and deploy large‑scale segmentation systems across multiple levels of granularity.
• Develop and optimize advanced clustering, classification, and representation‑learning models using statistical and machine‑learning techniques.
• Integrate and operationalize large, complex datasets—including census, geospatial, demographic, and unstructured data—to enrich segmentation workflows.
• Build robust model pipelines in distributed environments (PySpark, Databricks) and ensure scalability, reproducibility, and reliability.

Knowledge, Skills and Experience

• 8–12+ years of experience in data science with at least 3–4 years in a senior or lead role shaping analytical strategy or leading teams.
• Expertise in segmentation systems, including unsupervised learning (K‑Means, clustering), dimensionality reduction (PCA, Factor Analysis), and ML models (GLM, tree-based models, boosting).
• Proficient in Python, SQL, and R, with advanced hands‑on experience in distributed data processing using PySpark, Databricks, or similar platforms.
• Ability to work with diverse first‑party, third‑party, and large‑scale demographic datasets (e.g., Census data, area‑level data, unstructured sources).
• Experience in MLOps, feature stores, or production ML pipeline design.
• Background in geospatial modelling, representation learning, or scalable personalization engines.
• Expertise in data visualization using Tableau, Looker, Alteryx, or libraries like D3.js.

Skills

Cloud Platform, AWS, Azure, GCP, Python, R, SQL, PySpark, ML, DL, Neural Network, Databricks, Decision Trees, Boosting, Supervised learning, unsupervised learning, GMM, GLM, Bagging Trees, SVM

Qualification

Diploma or Bachelor’s degree in Computer Science, Information Technology, or a related field

Education

Bachelor Degree