At a Glance
- Tasks: Transform complex data into impactful insights for clients and teams.
- Company: Join Digitas, a leader in global marketing with a focus on connection.
- Benefits: Enjoy competitive benefits including pension, medical cover, and reflection days.
- Other info: Inclusive culture with excellent career growth and support for diverse backgrounds.
- Why this job: Shape real-world outcomes through innovative data science and collaboration.
- Qualifications: Strong stats background, hands-on experience in causal inference, and programming skills.
The predicted salary is between 60000 - 80000 £ per year.
At Digitas, we harness the power of connection to make a positive impact every day. We have a relentless focus on creating connections to help our clients’ businesses grow, connecting diverse people, ideas and expertise in innovative and exciting ways. We are making a positive impact with our amazing clients through our capabilities in Consulting, Products & Platforms, Customer Engagement and Digital Media.
We are hiring a Data Science Lead to help shape how we turn complex data into meaningful impact for our clients and teams. At Digitas, you’ll work at the intersection of analytics, experimentation and innovation—bringing clarity to challenging questions and driving confident decisions. This is a role where your expertise will directly influence how we design, measure and optimise real-world outcomes. You’ll join a collaborative environment where ideas are valued, and curiosity is encouraged.
Responsibilities
- Design and deliver rigorous causal inference studies, including natural and quasi-experiments that inform business decisions.
- Build and apply frameworks that quantify uncertainty in predictive models, enabling confident decision-making.
- Identify, assess and manage confounding variables in observational datasets.
- Develop robust statistical approaches to estimate causal impact across a range of client challenges.
- Translate business questions into structured experimental designs and analytical approaches.
- Partner with cross-functional teams to embed data science into product, marketing and consulting initiatives.
- Communicate findings clearly, turning complex analysis into actionable insights for technical and non-technical audiences.
Qualifications
- Strong grounding in statistics and quantitative methods, supported by relevant academic or professional experience.
- Hands-on experience applying experimental design and causal inference techniques to real-world data.
- Understanding of modern approaches to uncertainty estimation in machine learning (e.g. conformal prediction).
- Proficiency in Python, R, or similar programming languages used for data analysis.
- Familiarity with causal frameworks such as potential outcomes or causal graphs.
- Working knowledge of machine learning and how it integrates with causal reasoning.
- Clear and confident communicator, able to explain complex ideas in a simple and engaging way.
Digitas offers a wide range of benefits to support our employees. Full details are shared when you join, but highlights include core benefits such as Pension, Life Assurance, and Private Medical cover, alongside enhanced policies like Reflection Days and Shared Parental Leave.
At Digitas, we are proud to be an equal opportunities employer. We welcome and encourage applications from people of all backgrounds, and do not discriminate on the basis of race, ethnicity, nationality, religion or belief, disability, age, citizenship, relationship status, sexual orientation, gender identity, or any other protected characteristic. We are committed to providing a fair, accessible, and inclusive recruitment process.
Data Scientist employer: Publicis Groupe
Publicis Groupe is an exceptional employer, offering a dynamic work culture that fosters creativity and collaboration in the heart of Greater London. With a strong focus on employee growth, we provide comprehensive benefits such as Pension, Life Assurance, and Private Medical cover, ensuring our team feels valued and supported. Join us to lead innovative strategies for renowned brands like Disney, while enjoying a workplace that champions inclusivity and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨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 Publicis Groupe!
✨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 Data Scientist at Publicis Groupe.
✨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 Publicis Groupe.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist at Publicis Groupe, 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 Data Scientist
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 Publicis Groupe, 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 Publicis Groupe. 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 Publicis Groupe
✨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 Publicis Groupe!
✨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.