Manager Data Science

Mondelēz International
Birmingham
4 months ago
Applications closed

Related Jobs

View all jobs

Manager – Data and Data Science Strategy – Emerging Data and Capabilities

Audit Manager - Data Science. R00AOR05263

Data Scientist/Senior Data Scientist – Generative AI

Data Science Manager

Head of Data Science, Games Tech (Hybrid London)

Senior Analytics Manager: Lead Data Science, Hybrid

Description

Are You Ready to Make It Happen at Mondelēz International?

Join our Mission to Lead the Future of Snacking. Make It With Pride.

You will be crucial in supporting our business by leading a team of data scientists, supporting them in applying the best analytical methods to improve the statistical forecast and overcome business challenges. You will work with various stakeholders to determine how to use business data for business solutions/insights.

About the role

In this role you will:

Build and develop a high-performing team, fostering a culture of collaboration, continuous learning, and professional growth.  Mentor and coach team members to unlock their full potential by ensuring a supportive and inclusive work environment.  Support the team in analyzing and deriving value from data using application methods such as statistics, time series modelling, machine learning and data visualization.  Help the team determine, create and maintain the best time series / machine learning models be to use, taking into accountSKU demand behavior using segmentation strategies, to generate high quality statistical demand forecast with low forecast error and bias. Partner with Demand Planning teams in markets to understand business challenges, create valuable, actionable data insights, and communicate findings to the business. Collaborate with stakeholders toidentify and clarify business or technical questions that need to be answered. Provide feedback to translate and refine business questions into actions.

The experience we are looking for:

A desire to drive your future and accelerate your career and the following experience and knowledge: Proven leadership and people management skills, with at least 3 years of experience building and developing high-performing teams. 5+ years of experience in data science, preferably with a focuson time series forecasting,FMCG, Food & Beverages, Retail or similar industries with a proven track record of delivering effective business solutions. Experience in application of ML concepts and methodologies (particularlytime series modeling, but also regression, classification, feature engineering and selectionetc.) Proficiency in SAS, SQL, Python,and other programming languages to communicate effectively with technical teams.  Excellent communication and presentation skills, ability to explaincomplex analytical topics to both technical and non-technical stakeholders. Advanced English

What we offer

Exciting work in a multi-cultural team of bright minds. Global career opportunities. Flexible remote work options, or – if you prefer – access to one of our modern offices. All kinds of benefits depending on the location.

More about this role

What you need to know about this position:

What extra ingredients you will bring:

Education / Certifications:

Job specific requirements:

Travel requirements:

Work schedule:

Relocation Support Available?

Business Unit Summary

We value our talented employees, and whenever possible strive to help one of our associates grow professionally before recruiting new talent to our open positions. If you think the open position you see is right for you, we encourage you to apply!

Our people make all the difference in our succes

Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

Excited to grow your career?

We value our talented employees, and whenever possible strive to help one of our associates grow professionally before recruiting new talent to our open positions. If you think the open position you see is right for you, we encourage you to apply!

IF YOU REQUIRE SUPPORT TO COMPLETE YOUR APPLICATION OR DURING THE INTERVIEW PROCESS, PLEASE CONTACT THE RECRUITER

Job Type

RegularAnalytics & ModellingAnalytics & Data Science

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.