About the Role

As a Junior Data Scientist within the Global Modelling Unit – Market Strategy and Understanding (GMU MSU) team at Ipsos, you will be at the heart of building intelligent, data-driven solutions that power global research decisions. You will design and deliver end-to-end data science pipelines - from raw data ingestion to machine learning models and AI-assisted insight generation - helping our clients understand consumer behaviour and market trends.

You will be joining a highly collaborative team made up of Data Scientists, Statisticians, and Cloud Engineers based across the globe (Malaysia, UK, Poland, & Czechia). Day-to-day, you will work with both standard and complex survey datasets, applying machine learning, NLP, and AI techniques to extract meaningful patterns and build scalable solutions.

This is a fantastic opportunity to grow your career at the intersection of data science and market research - applying cutting-edge Python, ML, and LLM skills to real-world commercial challenges alongside a diverse, global team of experts.

Note: This role is primarily internally focused with minimal external client contact.

Your Mission

Build. support and deploy data science solutions - including ML models, segmentation pipelines, and AI-powered analytics that drive actionable insights for global research teams.
Collaborate seamlessly with our international cross-functional team to translate complex research questions into scalable, data-driven products.
Continuously develop your data science skillset across Python, R, machine learning, NLP, and modern AI - contributing to a culture of innovation and knowledge sharing.

Key Responsibilities

Data Science & Modelling: Design and execute end-to-end data science and advanced analytics projects, including machine learning-based customer segmentation, and predictive modelling to uncover actionable insights from complex datasets.
AI & LLM Integration: Leverage our scalable, developed AI pipelines and Large Language Models (LLMs) that process unstructured text, automate insight extraction, and enhance overall research quality.
Python Development: Write clean, efficient, modular and well-structured Python code (e.g., Pandas, NumPy, Scikit-learn) to build robust data pipelines, models, and analytical tools.
Data Manipulation: Receive and transform raw datasets, primarily in SPSS and Excel formats from data processing teams into well-structured inputs ready for modelling and advanced analysis.
Database Management: Utilise SQL to query, extract, and manipulate data from relational databases to support modelling and reporting workflows.
Operational Delivery: Take independent ownership of assigned data science deliverables end-to-end, ensuring accuracy, reproducibility, and timely outputs for the research teams.
Global Collaboration: Participate in team meetings and knowledge-sharing sessions, managing your time effectively across different time zones.

Qualifications

Essential Skills

Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Data Analytics, Computer Science, or a related quantitative field.
0–2 years of experience in a Data Science, Analytics, or related role (relevant internships or academic research projects are welcomed).
Machine Learning & Modelling: Foundational knowledge of ML concepts including clustering, classification, and regression, with the ability to apply them to real-world datasets.
Python Programming: Strong hands-on skills in Python for data manipulation, analysis, and modelling (e.g., Pandas, NumPy, Scikit-learn).
NLP & Text Analytics: Working knowledge of text analytics and NLP concepts; experience applying them to unstructured data is a plus.
Data Engineering: Good understanding of SQL for querying and setting up databases, alongside hands-on experience with SPSS and Excel data structures/formats.
Statistical Foundations: Comfortable applying core statistical methods (e.g., significance testing, correlation) as supporting tools within broader data science workflows.
Work Ethic: Accountable, resourceful, and proactive, with a strong commitment to meeting deadlines and overcoming operational obstacles.
Communication: Excellent written and verbal communication skills, with the ability to work effectively in a distributed, international team environment.
Professional working proficiency in English.

Desirable Skills (A Plus)

Applied AI & LLMs: Experience with or a strong interest in Large Language Models (e.g., OpenAI GPT, Claude) and prompt engineering techniques to enhance analytics workflows within our existing pipelines.
Cloud Experience: Hands-on experience or familiarity with Google Cloud Platform (GCP) is a strong advantage.
Deep Learning / Advanced NLP: Exposure to transformer-based models, embeddings, or fine-tuning pre-trained models for downstream tasks.

Ipsos is one of the world’s largest research companies and currently the only one primarily managed by researchers, ranking as a #1 full-service research organization for four consecutive years. With over 75 different data-driven solutions, and presence in 90 markets, Ipsos brings together research, implementation, methodological, and subject-matter experts from around the world, combining thematic and technical experts to deliver top-quality research and insights. Simply speaking, we help the biggest companies solve some of their biggest problems, serving more than 5000 clients across the globe by providing research, data, and insights on their target markets. And we are proud of our continuous efforts in making Ipsos the best place to work!

Data Scientist (GMU MSU)

Job Description