Senior Manager Data Science

At McCormick, we bring our passion for flavor to work each day. We encourage growth, respect everyone's contributions and do what's right for our business, our people, our communities and our planet. Join us on our quest to make every meal and moment better.

 

Founded in Baltimore, MD in 1889 in a room and a cellar by 25-year-old Willoughby McCormick with three employees, McCormick is a global leader in flavour. With over 14,000 employees around the world and more than $6 Billion in annual sales, the Company manufactures, markets, and distributes spices, seasoning mixes, condiments and other flavourful products to the entire food industry, retail outlets, food manufactures, food service businesses and consumers.

 

While our global headquarters are in the Baltimore, Maryland, USA area, McCormick operates and serves customers from nearly 60 locations in 25 countries and 170 markets in Asia-Pacific, China, Europe, Middle East and Africa, and the Americas, including North, South and Central America

Position Overview / Primary Purpose

Reporting to the Global ML & Data Science Director, the ML & Data Science Manager is responsible for providing strategic leadership, fostering innovation and ensuring ethical AI practices. This leader plays a pivotal role in driving the successful implementation of ML, forecasting and data science initiatives to achieve business objectives and maintain a competitive edge through strategic application of advanced technologies

Key Responsibilities

• Develop a comprehensive strategy for forecasting that aligns with the organization's overall goals and objectives
• Define a roadmap for implementation to deliver and scale forecasting approach across product groups 
• Lead a team of ~5-10 people and ensure team is on track and clear on work items, ways of working and deadlines
• Set up team to succeed by working with IT and stakeholders for project clarity and proper technology stack
• Establish KPIs and metrics to measure the performance and impact of predictive analytics.
• Ensure the availability and quality of data required for forecasting initiatives
• Establish processes for continuous improvement of ML and forecasting models, incorporating feedback and adapting to changing business needs
• Implement and enforce ethical AI practices, ensuring fairness, transparency, and accountability in forecasting processes

 

Additional / Secondary Responsibilities

1. Partner with IT and provide needed capacity & capability for McCormick’s digital transformation
2. Ad hoc participation in GBS Governance and Enterprise Digitalization governance as appropriate

 

Required Qualifications

Level of Education and Discipline
Bachelors in Mathematics, Statistics, Computer Science, Data Analytics/Science, or related field

 

Experience

• Technical knowledge for Data cloud environments (Azure or AWS), transformation, ML models and queries
• Leading global teams across different geographies
• Proficiency in Scrum or Lean methodology and ability to drive results using Lean thinking and Process Improvement tools
• At least 8 years of relevant experience and progressive leadership roles
• Working with Regional Leadership teams in establishing scorecards, KPIs and ML/ Forecasting solutions

 

Interpersonal Skills

• Strong communication and diplomacy skills to guide and influence others
• Strong analytical decision-making and direction-setting
• Experience working with regions and different cultures

 

Other Skills & Competencies

• Business acumen
• Able to manage ambiguity
• Ability to translate strategy into actionable information
• Flexible and able to manage concurrent priorities
• Strong problem-solving skills: leads others in problem-solving and root cause analysis
• Knowledge of emerging technologies and innovation
• Able to travel
• Fluent English is required

At McCormick, we have over a 100-year legacy based on our “Power of People” principle. This principle fosters an unusually dedicated workforce requiring a culture of respect, recognition, inclusion and collaboration based on the highest ethical value