At a Glance
- Tasks: Develop and implement complex data models to drive real customer outcomes.
- Company: Join dunnhumby, a global leader in Customer Data Science.
- Benefits: Enjoy flexible working hours, a comprehensive rewards package, and birthday off.
- Other info: Great opportunity for career growth and project management experience.
- Why this job: Make a measurable impact with cutting-edge technology in a collaborative environment.
- Qualifications: Degree in a quantitative field and strong programming skills in Python and SQL.
The predicted salary is between 60000 - 80000 £ per year.
dunnhumby is a global leader in Customer Data Science, working with major retailers and brands. We are seeking a Senior Applied Data Scientist to join our advanced data science team.
As a senior data scientist, you will be responsible for the ongoing implementation, support, and development of complex models and applications, working closely with clients and internal stakeholders to build scalable, reusable solutions that deliver measurable value.
What We Expect From You
- Degree in Statistics, Mathematics, Physics, Economics, or a related quantitative field
- Strong programming skills – Python and SQL are essential; PySpark experience is highly advantageous
- Experience with version control tools (e.g. GIT)
- Solid understanding of analytical technologies, tools, and techniques
- Excellent logical thinking and problem‑solving abilities
- Strong communication skills, with the ability to explain complex concepts clearly to non‑technical audiences
- Proven experience in statistical modelling and applying data science solutions to real client problems
- A passion for connecting technical work to real customer outcomes, delivering measurable impact
- Effective stakeholder management and the ability to build trusted relationships across teams
- Project Management and/or Team Leadership experience
- Background in retail analytics, especially exposure to Category Management (advantageous)
What You Can Expect From Us
You will enjoy a comprehensive rewards package, flexible working hours, and benefits such as birthday off. We invest in cutting‑edge technology and foster a collaborative, innovative environment.
Our Approach to Flexible Working
We support a healthy work/life balance and are open to discussing flexible working arrangements during the hiring process.
Senior Applied Data Scientist in London employer: hackajob
At dunnhumby, we pride ourselves on being a forward-thinking employer that champions innovation and collaboration within our advanced data science team. Our commitment to employee growth is evident through our comprehensive rewards package, flexible working arrangements, and investment in cutting-edge technology, all designed to foster a healthy work/life balance and empower our team members to make a meaningful impact in the world of Customer Data Science.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Applied Data Scientist in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like hackajob!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Applied Data Scientist at hackajob.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like hackajob.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Applied Data Scientist at hackajob, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Applied Data Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at hackajob, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at hackajob. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at hackajob
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at hackajob!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
