• Build the data function for a growing multi-product HealthTech platform • Define the company’s data strategy and strengthen how success is measured across product teams and the broader business • Assess the current setup, work directly with existing analysts, and shape the next stage of the function • Help Recare create a clearer picture of customer acquisition, product performance, and market growth • Connect product usage data to business performance • Turn data into actionable narratives for business reviews and product reviews • Lead a team of analysts, evaluate the current structure, and grow the function over time • Shape how data supports teams across product, finance, RevOps, and marketing • Define the right tooling and infrastructure for the company’s data needs • Collaborate with the AI engineering team on evaluation and quality measurement of AI outputs

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. Your Client We are looking for a Data Science Specialist to join a product-focused engineering team. In this role, you will work closely with data scientists, ML engineers, and domain experts to analyze complex datasets, understand model behavior, and drive improvements through data quality, structure, and insight-driven analysis. This position is highly hands-on and focuses on improving model performance through deep data understanding. Your Role Data Understanding and Representation Analysis - Analyze high-dimensional sensor and feature datasets using UMAP, t-SNE, PCA, and similar techniques - Identify clusters, anomalies, blind spots, distribution gaps, and class or environment mismatches - Diagnose dataset shift, domain drift, sparsity, and representation collapse Model-Aware Data Analysis - Perform data analysis aligned with classical ML models including XGBoost, SVR, k-NN, and tree-based models - Support analysis for deep learning models such as CNNs and Transformers - Analyze embeddings, confusion matrices, and model failure patterns to trace errors back to data issues Data Quality and Curation - Investigate imbalanced data, noisy sensor signals, mislabeled samples, and ambiguous cases - Develop approaches for improving weakly labeled or unlabeled data including clustering and pseudo-labeling - Perform data mining on large collections of field data to extract insights and patterns - Design processes for converting noisy or partially verified data into high-quality validated datasets Insight-Driven Improvements - Translate exploratory findings into clear recommendations for data filtering, relabeling, or new data collection - Advocate for and implement data-centric improvements to enhance model robustness - Work closely with engineering teams to integrate improved data workflows into ML pipelines Your Profile Minimum Qualifications Master’s or PhD in Data Science, Computer Science, Applied Mathematics, Statistics, Physics, or a related field 2–3+ years of hands-on data science experience with real-world ML datasets including time-series, images, video, or sensor data Strong proficiency in Python and core data science libraries such as NumPy, pandas, matplotlib, seaborn Experience using dimensionality reduction and representation analysis tools such as UMAP, t-SNE, PCA Experience analyzing data for classical ML and deep learning pipelines Strong understanding of ML fundamentals, evaluation methods, and diagnostic techniques Preferred Qualifications Experience with sensor or time-series data such as magnetic, radar, 3D, environmental, or IoT data Familiarity with scikit-learn preprocessing workflows Experience handling imbalanced datasets, label noise, sensor noise, and data drift Understanding of embedding analysis, feature importance, and model interpretability methods Experience working with data annotation teams or managing labeling processes Familiarity with MLOps or data versioning tools such as MLflow, Weights and Biases, or DVC What You Will Love About Working Here - We care about all our employees and want them to feel as comfortable as possible. That's why we offer them health insurance from the first days, regardless of the probationary period. - The gift from the company - Christmas holidays from 25 December to 31 December. - Сooperation with Superhumans center and Veteran HUB. Capgemini Engineering has supported the launch of psychological rehabilitation department of Superhumans. Our team also donated over UAH 500 000 prosthetics for three Ukrainian defenders. Currently, we support psychological counseling provided by the Veteran Hub, and we have implemented an internal policy making the company friendly to military and veterans with the assistance of the Hub. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. #LI-Remote

• Own the end to end pipeline, powering classification at scale (~900K mods), from labelling data to production models. • Turn raw data into structured, high-quality metadata that unlocks search, filtering, and personalisation. • Continuously improve model performance and data quality. • Build recommendation models and improve search relevance to help users find the right mods faster. • Leverage behavioural signals and unique datasets (e.g.dependency graphs) to power smarter personalisation. • Directly impact engagement by increasing downloads, retention, and overall activity.

Job Description Job Purpose: As a Lead Data Scientist within the Data Science Research team in the NIQ Product organization, you will drive definition and support of new products and methods development, and improvement initiatives. This position focuses on innovation in data processing methods for retail measurement and automation of existing statistical procedures. Job Responsibilities: - Define, plan and execute analyses regarding innovation initiatives, methodology development and improvement as well as process automation. - Prototype solutions and support pilot programs for R&D purposes, including trend analyses, representation/sampling, bias reduction, indirect estimation, data integration, automation, and generalization. - Test-driven development of scalable data processing applications. - Deliver high quality documentation of new methodologies and best practices. - Collaborate with experienced Developers, Data Scientists, and Technology engineers. - Support various Operations team as main users of our solutions. - Engage with stakeholders on scope, execution, data exchange, and outcomes for assigned projects. - Participate in multiple projects simultaneously. Machine Learning & Artificial Intelligence - Machine Learning: Knowledge of various algorithms and their appropriate application for prediction and classification. - Deep Learning: Understanding of neural networks and deep learning frameworks like TensorFlow and PyTorch. - GenAI and AgenticAI: Knowledge of available applications and programming packages for implementation of LLM based solutions and data processing automation. Data Visualization & Presentation - Data Visualization: The ability to create clear and compelling charts and graphs using tools like Tableau, Power BI, or Matplotlib to communicate findings to stakeholders. Databases & Cloud - Database Management: Proficiency with both SQL and NoSQL databases (like MongoDB) for data storage and retrieval. - Cloud Computing: Experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Requirements: - Extensive experience in trend analyses, multivariate statistics (parametric/non-parametric), sampling, bias reduction, indirect estimation, data aggregation techniques, automation, and generalization. - High proficiency in Python programming language including data analysis and statistical packages (Pandas, NumPy, Scikit-Learn). Good familiarity with Python standard library, especially unittest and argparse modules. - Experience with Spark or other big data processing solutions. - Experience in machine learning and GenAI / AgenticAI applications - Experience with cloud computing and storage (MS Azure preferred). - Experience with Docker and Linux command line. - Ability to quickly manipulate, analyze, and interpret large data sources. - Strong communication/writing skills with good English (working in a remote team with a global footprint). Preferred: - Experience in NIQ methodologies, data collection, platforms, research processes, and operations. Qualifications - Master degree in Statistics, Mathematics, Computer Science, Engineering or related fields with outstanding analytical expertise and strong technical skills. - At least 5 years of relevant work experience. Additional information Our Benefits - Flexible working environment - Volunteer time off - LinkedIn Learning - Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies. About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion Additional Information Our Benefits - Flexible working environment - Volunteer time off - LinkedIn Learning - Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies. About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion