Lead Data Scientist

NielsenIQ

About The Position

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 Senior Manager in the Data Science team, you will play a critical role in developing the next generation of retail measurement solutions 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. 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.

Requirements

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.
10 years of experience in data science/research
experience in independently leading and owning end-to-end research related projects
Vast 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.
Proficient in Python and its most common data science libraries.
Experience with cloud computing and storage software, ETL
Ability to lead and influence with other functional areas as a team and deliver results on time and per-spec.
Experience in designing experiments, prototyping as well as supporting pilot programs for R&D purposes.

Nice To Haves

PhD level in the area is a plus.
Domain in managing clients and proven experience of solving complex client requirements.
Strong Communication skills and ability to present and explain methodological and operational solutions to executive leadership.

Responsibilities

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.