Lead Data Scientist (Hybrid)

Nestlé • Arlington, VA

404d

About The Position

The Enterprise Analytics (EA) Lead Data Scientist at Nestlé USA is responsible for leveraging advanced analytics to drive profitable growth across the enterprise, particularly within the Manufacturing sector. This role combines business acumen with data science expertise to develop and implement predictive algorithms that enhance operational decision-making and problem-solving capabilities. The position involves mentoring junior staff, collaborating with various departments, and presenting analytical findings to leadership teams.

Requirements

• Undergraduate Degree in Computer Science, Engineering, Mathematics, Statistics, Business or a similar field; Master's degree preferred but relevant work experience may be considered in lieu of a Master's Degree.
• 5+ years of experience using various programming languages (R, Python, etc.) to develop and apply machine learning methods and algorithms to address business priorities, with a focus on consumer products preferred.
• Strong understanding of business operations and how to harness data and analytics to meet business needs.
• Experience in manufacturing operations, processes, data, and systems.
• Ability to develop and deploy advanced analytical models and algorithms that drive profitable growth at NUSA.
• Strong working knowledge of a variety of machine learning techniques (Regression, Clustering, Decision Tree, Neural Networks, Bayesian, etc.).
• Experience developing analytics solutions in Python, with hands-on experience leveraging Python's data manipulation, analysis, and visualization libraries.
• Proficiency in scripting in Python, including the ability to write efficient code to automate tasks, manipulate data, and perform various operations using Python libraries and frameworks.
• Strong understanding of object-oriented programming (OOP) in Python and how to effectively implement classes, objects, and inheritance hierarchies to create modular and reusable code.
• Experience visualizing/presenting data for partners using PowerBI, Tableau, or Streamlit.
• Familiarity with MLOps best practices for deploying, monitoring, and maintaining solutions in production.
• Passion for solving complex data problems and generating cross-functional solutions in a fast-paced environment.
• Proven examples of developing, selling, and sharing modeling concepts and software development best practices across team members to drive adoption.
• Experience in a mentorship role, focused on driving contribution beyond own models and projects.
• Good facilitation and presentation skills, including training delivery.
• Excellent oral and written communication skills, organizational and time-management abilities.
• High initiative, self-starter, and able to work with limited supervision.

Responsibilities

• Test and implement advanced analytics methods to derive insights that drive business growth.
• Drive the execution of AI solutions to address business needs.
• Drive EA priorities through rapid piloting and scaling of next-gen technologies.
• Incorporate the latest data science thinking into NUSA's solutions and models.
• Collect, cleanse, and understand complex data sources to enable proper analytical modeling.
• Research, design, develop, test, and implement data science methodologies across a wide range of business applications.
• Define and develop programming for self-service decision support solutions that leverage predictive, prescriptive, and scenario optimization tactics.
• Manage Special Projects, Pilots, Proof of Concepts, and Ad-hoc project work leading the charge from idea to delivered data science capability.
• Participate in the evaluation, intake, design, and integration strategy between multiple commercial functions and data sources for varying Nestlé businesses.
• Conduct proper stakeholder management to ensure all parties are aligned and updated throughout project life cycle.
• Design and build advanced visualization tools that will simplify the outputs of the models, with the goal of being integrated into a self-service operational model across the business stakeholders.
• Develop professional presentations and project status reporting appropriate for their intended audience.
• Coach analysts and junior data scientists in addressing modeling issues identified by the business stakeholders.
• Develop reusable assets that can be leveraged across the data science team.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Food Manufacturing
• Education Level: Bachelor's degree