Data Science Engineering Manager

dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First.

Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail – one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First.

dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro.

We’re looking for Data Science Engineering Manager who expects more from their career.

Our research Data Science team are responsible for delivering personalized recommendations for global retailers, enhancing the shopping experience for millions of customers around the world.

This role involves engaging in the full lifecycle of machine learning projects, from inputting into the open source tooling strategy to taking research solutions developed by data scientists into production, particularly for recommender systems. You will be responsible for developing Python libraries, ensuring their usability across our team of data scientists, and overseeing the deployment of machine learning models into production environments.

Key Responsibilities:

• Develop and maintain Python and PySpark libraries for use in Data Science projects.

• Oversee the productionization of machine learning models

• Research, evaluate, and (when appropriate) release open-source MLOps tools to our Data Science team

• Maintain and optimize our data processing and machine learning pipelines, primarily using Python and PySpark.

• Lead, mentor, and manage a team of Data Science engineers, fostering a collaborative and productive work environment.

• Drive team objectives, aligning them with common goals across product, science and engineering

• Implement and oversee DevOps practices, including continuous integration and continuous deployment (CI/CD) pipelines.

• Ensure adherence to best practices in coding, testing, and deployment.

Technical Skills Required:

• Proficient in Python and experienced with PySpark.

• Strong experience with Git and version control systems.

• Strong understanding of data structures, algorithms, and software engineering principles.

• Familiarity with DevOps practices and tools for CI/CD.

• Knowledge of MLOps tools such as MLFlow, Kubeflow

• Knowledge of Observability and Telemetry tools such as Evidently and Great Expectations.

• Familiarity with big data technologies and tools.

• Experience with cloud services (e.g., GCP, Azure) is a plus.

• Desirable- Understanding of machine learning algorithms and frameworks (e.g., Sklearn, XGBoost, Tensorflow, PyTorch).

What you can expect from us

We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off.

You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn.

And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One and dh Thrive as the living proof. Everyone’s invited.

Our approach to Flexible Working

At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work.

We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process.