Artificial Intelligence Manager - F&B

Minneapolis, MN, USA|Remote, Onsite

Job Overview

Employment Type

Full-time

Compensation

Salary

Range $42,400.00 - $68,600.00

Benefits

Health Insurance

Dental Insurance

Paid Time Off

retirement plans

Performance bonus

Career development programs

hybrid work schedule

Job Description

Ecolab Digital is a division of Ecolab, a global leader in water, hygiene, and infection prevention solutions and services. Ecolab supports nearly three million commercial customer locations worldwide, delivering comprehensive solutions and data-driven insights to improve food safety, maintain clean and safe environments, optimize resource use, and advance operational efficiencies for customers primarily in the food, healthcare, hospitality, and industrial sectors. With over 45,000 associates and an annual sales volume of $13 billion, Ecolab operates in more than 170 countries. The organization is renowned for its commitment to innovation, sustainability, and customer success. Working at Ecolab offers professionals meaningful challenges,...

Job Requirements

bachelors degree in data science, economics, math, statistics, computer science or related field with an emphasis on analytics and 10 years of experience in progressive data science or AI roles or master’s degree with 7 years of experience in progressive data science or AI roles
3 years’ experience of a proven track record leading and executing high-impact, technically complex projects and teams
experience with full lifecycle of data science product development
3 years experience of working with business stakeholders
4 years’ experience with python
experience managing teams with diverse skill sets and a portfolio of products or priorities to guide and ensure accountability within the team
no immigration sponsorship is available for this role at this time

Job Qualifications

Bachelors Degree in Data Science, Economics, Math, Statistics, Computer Science or related field with an emphasis on analytics and 10 years of experience in progressive data science or AI roles or Master’s degree with 7 years of experience in progressive data science or AI roles
Demonstrated interconnected disciplinary knowledge of digital solution development
Excellent communication and presentation skills, effectively partnering and delivering results to a broad spectrum of stakeholders
Ability to thrive in an ambiguous environment, embracing change and utilizing proven reasoning in balancing practical business needs and analytics rigor
Well-developed and proven leadership, strategic thinking, and business acumen
Proficiency in the Microsoft Azure Suite, including Databricks and PowerBI
Working knowledge of DevOps, git, Snowflake, and distributed compute platforms
Proficiency with time series and advanced sensing data
Experience in consulting and or product management
Expertise in building and scaling intelligent systems leveraging LLMs, embedding pipelines, and agent workflows
Proficiency in Python 3.11+, LLM Apis, cloud-native engineering (Azure preferred), and scalable architecture principles

Job Duties

Lead, manage, and mentor a high-performing team of data scientists, AI engineers, and data analysts ensuring excellence in technical execution and professional development
Partner to define, implement, and refine the AI and analytics strategy and roadmap, aligning with the organization's long-term goals, evolving business needs, and overall digital product vision
Utilize an extensive foundation of AI methodologies and latest advancements to bring creativity, quality and technical ownership to drive the team's development, implementation, and health of solutions
Provide clear, consistent communication and presentation to various product stakeholders driving strategic alignment, AI education, and impact-based decisions
Work within an agile global resource model, planning for and delivering against strategically aligned initiatives as a team
Ensure the scalability, reliability, and robustness of AI solutions through advanced model development, AI system design, deployment, and monitoring practices within the team