Data Scientist – Sensory Modeling

NielsenIQ•Massachusetts, MA

22h•Remote

About The Position

As a Data Scientist – Sensory Modeling, you will play a critical role in advancing NIQ’s sensory intelligence capabilities by developing cutting-edge statistical and machine learning models. This role focuses on translating complex sensory and consumer data into actionable insights that inform product innovation and development across FMCG categories and markets.

Requirements

Master’s or Ph.D. in Statistics, Data Science, Computer Science, or a related field
Strong foundation in probability theory and Bayesian inference
Experience with hierarchical/mixed-effects models and latent variable modeling
Hands-on experience with variational inference and/or MCMC methods
Experience working with consumer or sensory data, ideally within FMCG or adjacent industries
Understanding of sensory data structures and methodologies (e.g., hedonics, JAR, CATA, trained vs. untrained panels)
Proficiency in Python and/or R
Experience with machine learning techniques
Strong data engineering and SQL capabilities
Experience working in cloud environments (e.g., Azure)
Excellent communication skills with the ability to translate complex findings into clear business insights

Nice To Haves

Experience in sensory and consumer science or consumer research analytics
Experience designing experiments for sensory and consumer studies
Experience integrating multi-study datasets (sensory, consumer, and product data)
Familiarity with marketing science and innovation analytics
Understanding of end-to-end product development and innovation processes
Experience building reusable, scalable modeling frameworks
Experience addressing panelist effects, scale-use bias, and cross-cultural differences
Proven ability to integrate heterogeneous datasets into unified modeling frameworks
Exposure to formulation or ingredient-level data and its relationship to sensory perception

Responsibilities

Develop advanced statistical and machine learning models to analyze and predict consumer sensory preferences across products, markets, and demographics
Design and implement models for latent harmonization of sensory and consumer datasets across studies, methodologies, and geographies
Build and apply Bayesian and hierarchical/mixed-effects models to estimate liking and sensory attribute performance
Develop frameworks for partial pooling and cross-product generalization
Translate sensory panel data into probabilistic predictions aligned with reference populations
Partner with research and client success teams to design effective consumer sensory studies and experimental frameworks
Validate and calibrate models to ensure robustness, interpretability, and business relevance
Prototype and productionize scalable analytics pipelines
Automate data harmonization and reporting processes across sensory and consumer datasets
Communicate insights clearly to stakeholders, translating analytical outputs into actionable R&D and product development recommendations
Stay current with advancements in Bayesian modeling, machine learning, and sensory science