Data Scientist

Ipsos North America

Data Scientist at Ipsos providing analytical input and integrating new data science tools. Collaborating globally to offer data-driven solutions for clients in a fast-paced environment.

Posted 6/18/2026full-timeKuala Lumpur • 🇲🇾 MalaysiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Provide analytical input and explain methods clearly to internal teams.
Guide and support the development of proposals by providing methodological ideas and data science recommendations.
Drive the integration of new tools, including GenAI, synthetic data models, and automation solutions, to meet client needs.
Work closely with specialized data science teams across multiple countries to provide excellent service in a fast-paced environment.
Lead the execution of day-to-day requests by writing clean, well-structured Python code to prepare data and run models.
Support the setup, execution, and quality control of analytical pipelines, checking data and outputs thoroughly.
Develop working knowledge of GenAI tools, APIs (e.g., LiteLLM, OpenAI, Langchain), and LLM-based workflows.
Create analytical deliverables such as code, outputs, and documentation while continuously seeking improvements.
Produce accurate, well-structured analytical outputs and write commentary to provide recommendations.
Prepare, plan, and prioritize tasks effectively using tools like Jira to ensure deliverables are sent to schedule.
Apply Ipsos’ quality, safety, and MRS Code of Conduct principles in all project work.

Requirements

What you’ll need

Degree in Data Science, Statistics/Mathematics, Computer Science, Actuarial Science, or related quantitative studies.
Running and executing code within JupyterLab environments and managing virtual machine instances.
Training and deploying models using GPUs accessed through Google Cloud Platform (GCP) services like Vertex AI.
Fine-tuning GenAI models/LLMs for specific use cases and implementing RAG.
Using Git and GitHub to manage code changes and collaborate with others.
Proficiency in Python, R, SQL, and Google Cloud Platform is essential.
Understanding of coding principles and design patterns to write clean code.
Knowledge of designing agent architectures to optimize the use of GenAI models/LLMs.

Benefits

Comp & perks

Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonRSQLGenAIsynthetic data modelsanalytical pipelinesJupyterLabGoogle Cloud PlatformVertex AILLM-based workflows

Soft Skills

analytical inputmethodological ideascommunicationleadershipcollaborationtask prioritizationquality controlproblem-solvingadaptabilityattention to detail