Data Scientist (GMU MSU)

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.