Senior Data Scientist

Job description

Our Audience Activation team develops data science solutions that help the business identify the right individuals, households, and geographic areas for campaign activation. We design robust predictive models to identify and prioritize relevant audiences, estimate audience potential, and support the measurement and prediction of campaign outcomes. As a Senior Data Scientist, you will operate at the intersection of Data Science, Product, Engineering, and Commercial teams. You will work closely with Product teams to translate business requests into clearly defined and solvable analytical problems, design scalable modeling solutions, and communicate findings in a lucid and actionable manner. You will also collaborate closely with Data Engineers and Machine Learning Engineers to ensure that Data Science solutions can be productionized, monitored, and operated reliably at scale. As a Senior Data Scientist, you will have the following primary responsibilities: • Own Data Science solutions across their full lifecycle, including problem definition, exploratory analysis, solution design, model development, validation, productionization, monitoring, and continuous improvement. • Partner with Product teams to understand business objectives, challenge assumptions, clarify requirements, and translate ambiguous requests into well-defined analytical problems, hypotheses, modeling approaches, and success criteria. • Assess whether a business problem requires predictive modeling, statistical analysis, experimentation, rules-based logic, or a combination of approaches along with designing robust model validation strategies and define appropriate technical and business performance metrics. • Evaluate the suitability, representativeness, strengths, and limitations of available datasets. Identify and appropriately address issues such as missing data, sampling bias, weighting, class imbalance, data leakage, and population drift. • Translate model outputs and analytical findings into clear business recommendations, explaining complex methodologies, assumptions, limitations, and trade-offs to both technical and non-technical audiences. • Work closely with Data Engineers and Machine Learning Engineers to convert analytical prototypes into scalable, maintainable, and production-ready ML solutions. • Mentor junior team members and support knowledge sharing across the wider Data Science community. • Identify opportunities to improve existing methodologies, processes, frameworks, and tools. • Stay informed about developments in audience analytics, machine learning, campaign optimization, experimentation, causal inference, and scalable ML engineering. • Foster knowledge exchange within the company. Present GfK's Data Science expertise at conferences and workshops   Now you know what a Data Scientist does. What skills, qualifications & experience do you need for this job?  • You typically have a Master's degree or PhD that reflects modeling and statistics skills and 7+ years of experience in Data Science, Statistics and ML models.  • You enjoy communicating complex methodology and technology to tech and non tech audiences  • You have expert statistical / machine learning modeling skills (e.g. statistical tests, classification, predictive modelling, handling of missing data, sampling, weighting)  • You have experience with an analytical programming language (Python) and the respective ecosystem  • Practical experience with Azure Databricks, including the development and execution of Data Science workflows in a collaborative environment. • Experience working with Apache Spark, PySpark, or an equivalent distributed data-processing framework. • Working knowledge of SQL and experience querying, joining, transforming, and validating large datasets. • Experience developing models and analytical workflows on large-scale datasets. • An understanding of how machine learning solutions are moved from experimentation into production environments. Besides the things we really expect you to have, there are some things which would be amazing if you have experience with them:  • Advanced software development skills (unit testing, CI/CD, Git)  • Basic skills regarding database handling as SQL  • Basic knowledge of the always evolving Data Science ecosystem and its frameworks  • A meaningful project, where you learn every day and show the team what you've got.  • The possibility to be part of a talented team, working with experienced individuals.  • A nice place to work, where we foster training, and personal development.  • Flex Office: a mix of remote and in-office work to boost our productivity and promote a healthy work-life balance  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