Senior Data Scientist

The Kraft Heinz Company
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist - National Security (TIRE) based in Cheltenham/Hybrid

Description

Are you a talented and driven Data Scientist with expertise in machine learning and a passion for building robust pipelines for demand forecasting? We are seeking a skilled individual to join our dynamic team at Kraft Heinz. Join our team and make an impact by leveraging machine learning and demand forecasting to drive data-driven decisions and optimize our business operations.

What's on the Menu?

As aSenior Data Scientist, you will be a key contributor on demand forecasting team. You will build and test statistical and machine learning models to accurately predict demand from our retailers. The models you build will be deployed into a production setting where your models will drive value across all our brands. You will provide updates and results to the Product Owner and Data Science Lead on the progress of your work while partnering with the business users to identify modeling opportunity areas.

Key Ingredients:

Utilize your strong analytical skills and machine learning expertise to develop advanced time-series models for demand forecasting. Collaborate with cross-functional teams to identify and define business problems related to demand forecasting. Conduct exploratory data analysis and feature engineering to extract valuable insights from complex datasets. Develop and implement machine learning algorithms to optimize demand forecasting accuracy and efficiency. Evaluate and fine-tune models by applying statistical methods and running experiments on real-world data. Communicate findings and insights to team members and work with the team to define modeling next steps

Recipe for Success: Apply if it sounds like you!

Master's degree in Computer Science, Statistics, Mathematics, or a related field. 2+ years experience with predictive modeling time-series, machine learning, statistical modeling Experience building demand forecast models Proficiency in programming languages such as Python and R, as well as libraries like scikit-learn knowledge on factors that influence shipment demand Proficient in SQL and working with relational databases. Experience using cloud-based services such as AWS, Azure, or Google Cloud Excellent problem-solving skills and ability to think critically about complex business challenges. Strong communication skills Proven ability to work effectively in a collaborative, fast-paced environment.

We hope to find you a seat at our table!

Location(s)

Amsterdam, London - The Shard

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.