Senior Commercial Data Scientist

Nestle Operational Services Worldwide SA•St. Louis, MO

9d•$118,422 - $166,343

About The Position

As a Senior Commercial Data Scientist at Nestlé Purina, you will apply data science, machine learning, and emerging AI capabilities to commercial and marketing challenges. You will bring a consumer perspective to analytical work and partner with marketing, brand, sales, and other commercial teams to turn business questions into analytical solutions and measurable outcomes. The role uses data and analytics in areas including consumer engagement, media, personalization, pricing and promotion, and digital commerce. You will serve as a hands-on consultant to commercial partners, design and implement statistical, predictive modeling, machine learning, and AI solutions, explore Generative AI applications, and help move solutions from experimentation into production under established AIOps/MLOps, monitoring, and model-governance practices. You will also contribute to reusable frameworks and share knowledge with other data scientists.

Requirements

Bachelor's degree in Data Science, Marketing Analytics, Applied Statistics, Economics, Computer Science, or a related field.
At least 2 years of experience working directly with business stakeholders to translate ambiguous business problems into analytical approaches and communicate technical findings in clear, business-relevant terms.
At least 5 years of professional experience, including at least 3 years applying data science, advanced analytics, or machine learning to marketing, consumer, commercial, e-commerce, sales, or related customer-facing business problems.

Nice To Haves

Master's or PhD in Data Science, Applied Statistics, Marketing Analytics, Economics, Computer Science, Business Administration, or a related field.
Experience operationalizing AI solutions through AIOps/MLOps frameworks, model governance, and enterprise AI lifecycle management.

Responsibilities

Consult with brand, marketing, sales, and category teams to understand challenges, clarify ambiguous problems, identify analytical opportunities, and translate commercial priorities into data science and AI solutions.
Design, develop, validate, and implement statistical, predictive modeling, machine learning, and AI solutions for consumer-facing, go-to-market, commercial, and marketing problems.
Explore and apply Generative AI capabilities to commercial and marketing opportunities, collaborating with technical experts when specialized architecture or engineering expertise is needed.
Work within established AIOps/MLOps, monitoring, and model-governance practices to help move solutions from experimentation into production.
Use and contribute to reusable frameworks, tools, and best practices that accelerate development and scale successful solutions.
Share knowledge with other data scientists and stay current on emerging AI and analytics approaches relevant to commercial and marketing applications.