Research Data Scientist

Research Data Scientist

Full-Time 50000 - 70000 £ / year (est.) No working from home possible
Limelight Health

At a Glance

  • Tasks: Create innovative data science solutions and apply machine learning techniques to real-world business problems.
  • Company: Join dunnhumby, a global leader in Customer Data Science with a collaborative culture.
  • Benefits: Enjoy flexible working hours, your birthday off, and a comprehensive rewards package.
  • Other info: Diverse and inclusive environment with excellent career growth opportunities.
  • Why this job: Make an impact on global retailers while working with cutting-edge technology and passionate experts.
  • Qualifications: Master’s degree in relevant fields and experience with machine learning and programming.

The predicted salary is between 50000 - 70000 £ per year.

hackajob is collaborating with Dunnhumby Ltd to connect them with exceptional professionals for this role. Dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers.

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, Nestlé, Unilever and Metro. We’re looking for a talented Research Data Scientist who expects more from their career. It’s a chance to extend and improve Dunnhumby’s world class science capabilities. It’s an opportunity to work with a market‑leading business to explore new opportunities for us and influence global retailers and suppliers.

Joining our team, you’ll work with world class and passionate people to apply machine learning and statistical techniques to business problems. You’ll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You’ll have the opportunity to present results to a variety of internal stakeholders and will apply these techniques and algorithms to create Dunnhumby science solutions that can be delivered across our clients and engineered into science modules.

This role will be focussed across insight automation and product assortment, with applications of science including identifying new and growing product needs, optimising the mix of products, predicting the impact of changes, product attribute generation and applications of generative AI for product support and insights.

What You'll Be Doing

  • Create new science‑based solutions that can be captured as science modules and applied across clients, with support from senior team members.
  • Pick up new machine learning approaches, such as regularised regression, clustering or tree‑based ensembles, graph‑based approaches, natural language processing and neural network techniques and apply them on client data.
  • Perform exploratory data analysis to characterise and visualise datasets.
  • Extend and develop programming skills, in languages such as Python and Spark, to develop efficient science code for science modules.
  • Help identify new opportunities within the Data Science space for future Dunnhumby solutions.
  • Implement advice from colleagues to resolve challenges.
  • Follow Quality Assurance processes, ways of working and meet coding standards.
  • Ensure smooth running of your projects, working with senior team members for direction.
  • Build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.

Who You’ll Get To Work With

  • Within Dunnhumby you’ll primarily work with Applied and Research Data Scientist teams.
  • Data Science Engineering teams.
  • Product and Client teams where required.

What You'll Need

  • Master’s degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
  • Experience with machine learning techniques such as regularised regression, clustering or tree‑based ensembles, and the ability to implement them through libraries.
  • Experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL.
  • Experience with or ability to quickly learn open‑source software including machine learning packages, such as Pandas and scikit‑learn, along with data visualisation technologies.
  • A willingness to present your work to both technical and non‑technical audience and to contribute to the wider data science community.

A Plus If You Also Have

  • PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
  • Experience in retail sector.

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, dh Enabled and dh Thrive as the living proof. We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you.

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.

Research Data Scientist employer: Limelight Health

Dunnhumby is an exceptional employer that champions innovation and collaboration, providing a dynamic work environment for Research Data Scientists. With a commitment to employee growth, flexible working options, and a diverse culture, you will have the opportunity to work with cutting-edge technology and contribute to impactful projects for leading global brands. Join a team where your contributions are valued, and enjoy a comprehensive rewards package that goes beyond expectations.

Limelight Health

Contact Details:

Limelight Health Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Data Scientist

Network Like a Pro

Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at dunnhumby. Building relationships can open doors that applications alone can't.

Show Off Your Skills

Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving machine learning and data analysis. Share it during interviews to impress the hiring team.

Prepare for Technical Interviews

Brush up on your coding skills and be ready to tackle technical challenges. Practice common data science problems and algorithms, especially those related to Python and machine learning techniques. We want you to shine!

Follow Up After Interviews

After your interview, don’t forget to send a thank-you email! It’s a great way to express your appreciation and reiterate your interest in the role. Plus, it keeps you fresh in their minds as they make decisions.

We think you need these skills to ace Research Data Scientist

Machine Learning
Statistical Techniques
Data Analysis
Model Validation
Exploratory Data Analysis
Programming in Python
Spark

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Research Data Scientist role. Highlight relevant experience and skills, especially in machine learning and programming languages like Python. We want to see how you can contribute to our team!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with dunnhumby's mission. Let us know what excites you about this opportunity!

Showcase Your Projects:If you've worked on any interesting projects or research, make sure to include them in your application. We love seeing practical applications of your skills, especially those involving machine learning techniques or data analysis.

Apply Through Our Website:For the best chance of success, apply directly through our website. This ensures your application gets to the right people quickly. Plus, it shows us you're serious about joining our team at dunnhumby!

How to prepare for a job interview at Limelight Health

Know Your Data Science Stuff

Make sure you brush up on your machine learning techniques like regularised regression and clustering. Be ready to discuss how you've applied these methods in past projects, as well as any programming languages you're comfortable with, especially Python and Spark.

Show Off Your Problem-Solving Skills

Prepare to talk about specific challenges you've faced in data analysis and how you tackled them. Think of examples where you used exploratory data analysis to derive insights or improve a process, and be ready to explain your thought process clearly.

Communicate Like a Pro

Since you'll be presenting results to both technical and non-technical audiences, practice explaining complex concepts in simple terms. Use visuals if you can, and be prepared to answer questions that might come from different perspectives.

Be Ready to Collaborate

Dunnhumby values teamwork, so think about how you've built relationships in previous roles. Be ready to share examples of how you've worked with others to achieve common goals, and show your enthusiasm for contributing to a collaborative environment.