Lead Data Scientist

Company Description

In 100 countries around the world, NielsenIQ provides clients the most complete understanding of how the FMCG market evolves and what consumers buy. As a global leader in measurement and information, we believe providing our clients a precise understanding of the consumer is the key to making the right decisions -- decisions that can lead to profitable growth. At NielsenIQ, we’re always innovating to keep pace with emerging market trends and the increasingly diverse, demanding and connected consumer.  

Being a Lead Data Scientist in the Data Science team, you will play a critical role in developing the next generation of retail measurement solutions (focused around E-commerce),  we offer our clients, powered by algorithms, ML and AI and leveraging large volumes of internal data, client data and third party data. 

You’ll be actively participating with other team members in the overall Product creation process. From ideation through Proof Of Concept and experimenting for methodological development, through prototyping and productionalization, to “Go to Market” strategy, you’ll be learning and exploring the newest technologies & applications for data architecture, and data modelling solutions. You will work alongside a group of talented individuals with different areas of expertise including best in class data scientists, product managers, and data collection specialists with the main purpose of accelerating innovation.  

Job Description

On a daily basis you’ll be expected to: 

• Work across functions, including with other data scientists specializing it different areas, on various projects, including R&D and automation to solve the business needs of the day 

• Translate Clients’ requirements to actionable solutions or products  

• Ideate and develop solutions for the product innovation pipeline 

• Define the given business problem as a scientific research problem 

• Define and own the roadmap of R&D and prototyping solutions 

• Research solutions, set and execute experiments, prototype the solution and support Technology team on productionalizing them  

• Build statistical and analytical models (including ML/AI approaches) as prototypes and POCs to address specific client business needs 

• Test and optimize those models using big data. Fine tune parameters and iterate. 

• Document the solution and experimentation to arrive to it, and create specifications for Technology team to productionize it 

• Read, write, comment, maintain, and share legible and quality computer code utilized in prototyping and suctioning. 

Qualifications

Role requirements:  (E=essential, P=preferred) 

• E - Bachelors or Masters degree or higher in Computer Science, Data Science, Statistics, Mathematics, Engineering or related field with requiring outstanding analytical expertise and strong technical background. PhD level in the area is a plus. 

• E – 3-5 years of experience in data science/research 

• E – Good knowledge of statistical and machine learning methodologies: Sampling theory, Probability Theory, Variation analysis, Outlier identification techniques, Regressions, Classification, Time series analysis, Clustering, Monte Carlo simulations, Neural Networks, etc. 

• E - Proficient in Python and its most common data science libraries. 

• E - Ability to collaborate with other functional areas as a team and deliver results on time and per-spec. 

• E – Experience in designing experiments, prototyping as well as supporting pilot programs for R&D purposes.  

• P -Strong Communication skills and ability to present and explain methodological and operational solutions to executive leadership. 

Additional Information

This role offers flexible working mode (1per week at the office - 4 days from home)

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 mitiga