Lead Data Scientist

Company DescriptionIn 100 countries around the world, Nielsen IQ 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 Nielsen IQ, we're always innovating to keep pace with emerging market trends and the increasingly diverse, demanding and connected consumer.
Being a Principal 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 dayTranslate Clients' requirements to actionable solutions or productsIdeate and develop solutions for the product innovation pipelineDefine the given business problem as a scientific research problemDefine and own the roadmap of R&D and prototyping solutionsResearch solutions, set and execute experiments, prototype the solution and support Technology team on productionalizing themBuild statistical and analytical models (including ML/AI approaches) as prototypes and POCs to address specific client business needsTest 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 itRead, write, comment, maintain, and share legible and quality computer code utilized in prototyping and suctioning.
QualificationsRole

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.
Ph D level in the area is a plus.
E – 5
- 8 years of experience in data science/researchE – 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 InformationThis role offers flexible working mode (1per week at the office
- 4 days from home)

Salary:
**,00 – €** gross per year.
This role might also be eligible for a performance-based bonus.
Placement within the range will depend on objective criteria including experience, skills, and internal equity considerations.
We are committed to equal pay and pay transparency.
Remuneration decisions are made using gender-neutral and objective criteria.
Our BenefitsFlexible working environmentVolunteer time offLinked In LearningEmployee-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