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.
- Why this job: Make an impact on global retailers while working with cutting-edge technology and passionate teams.
- Qualifications: Master’s degree in relevant fields and experience with machine learning and programming.
- Other info: Diverse and inclusive environment with excellent career growth opportunities.
The predicted salary is between 50000 - 70000 £ per year.
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
- 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: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current or former employees at dunnhumby on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your machine learning techniques. Be ready to discuss how you've applied them in real-world scenarios. We want to see your passion and expertise shine through!
✨Tip Number 3
Show off your coding skills! If you’ve got a GitHub profile, make sure it’s up to date with your projects. This is a great way to demonstrate your programming prowess and problem-solving abilities.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the dunnhumby team.
We think you need these skills to ace Research Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Research Data Scientist role. Highlight relevant experience, especially in machine learning and programming, and don’t forget to showcase any projects that demonstrate your skills!
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. Keep it engaging and personal – we want to see your personality!
Showcase Your Skills: Don’t just list your skills; show us how you’ve used them! Include specific examples of projects or challenges where you applied machine learning techniques or programming languages like Python. We love seeing real-world applications!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at hackajob
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning techniques, especially those mentioned in the job description like regularised regression and clustering. Be ready to discuss how you've applied these methods in past projects or how you would approach a specific problem using them.
✨Show Off Your Coding Skills
Since programming is key for this role, practice coding in Python and get familiar with libraries like Pandas and scikit-learn. You might be asked to solve a coding challenge during the interview, so being comfortable with data manipulation and analysis will give you an edge.
✨Prepare to Present
You'll need to present your findings to both technical and non-technical audiences, so practice explaining complex concepts in simple terms. Think of examples from your experience where you successfully communicated your results and how they impacted decision-making.
✨Understand Dunnhumby's Culture
Familiarise yourself with dunnhumby’s values and their approach to customer data science. Show enthusiasm for their mission and be prepared to discuss how you can contribute to their goals, especially in areas like insight automation and product assortment.