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- Tasks: Lead data science projects, applying statistical methods to drive insights and decisions.
- Company: Join Digitas, a leader in global marketing, making impactful connections for top brands.
- Benefits: Enjoy remote work options, reflection days, family-friendly policies, and wellness support.
- Why this job: Be part of a dynamic team shaping business strategies through innovative data solutions.
- Qualifications: Advanced degree in a quantitative field and 3+ years of relevant experience required.
- Other info: Hybrid working model with additional perks like birthday leave and agency discounts.
The predicted salary is between 43200 - 72000 ÂŁ per year.
BRAND:BRAND: Digitas UK
Job Function:Job Function: Data Sciences
Location:Location: London, United Kingdom
Experience Level:Experience Level: Specialist
Workplace Type:Workplace Type: Hybrid
Company descriptionAt Digitas, we harness the power of connection to make positive impact everyday. We have a relentless focus on creating connections to help our clients\â businesses grow, connecting diverse people, ideas and expertise in innovative and exciting ways.
We are making positive impact with our amazing clients, through our capabilities in Consulting, Products & Platforms, Customer Engagement and Digital Media.
Part of Publicis Groupe, and a Leader in Gartner\âs Magic Quadrant for Global Marketing Agencies, we\âre proud to work with some of the world\âs leading brands.
Digitas. Experience the power of connection.
Our CommitmentDigitas is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation or gender identity.
OverviewWe\âre hiring for a Lead Data Scientist! You will play a crucial role in applying cuttingâedge statistical methods to uncover insights and drive dataâinformed decisions. You\âll be responsible for designing robust experiments, applying causal inference, and using conformal prediction techniques to support our mission to deliver reliable, actionable analytics that shape business strategy.
Responsibilities
Design and analyse causal inference experiments using both randomized and quasi-experimental methods
Develop conformal prediction models to quantify uncertainty in machine learning predictions
Identify and account for confounding variables in observational studies
Create and apply statistical frameworks to estimate causal effects accurately
Collaborate with product, engineering, and business teams to design rigorous experiments
Present insights and methodologies in a clear and actionable way to stakeholders
Translate complex data challenges into impactful, dataâdriven solutions
Qualifications
Advanced degree (MS/PhD) in a quantitative field with strong statistical expertise
3+ years of handsâon experience applying statistical methods to realâworld data
Deep knowledge of experimental design and observational study techniques
Strong understanding of conformal prediction theory and applications
Proficient in Python or R, with experience in statistical and machine learning libraries
Familiarity with causal inference frameworks (e.g., potential outcomes, doâcalculus)
Clear communicator, able to explain complex statistical ideas to nonâtechnical audiences
Additional informationDigitas has fantastic benefits on offer to all of our employees. In addition to the classics, Pension, Life Assurance, Private Medical and Income Protection Plans we also offer:
WORK YOUR WORLD opportunity to work anywhere in the world, where there is a Publicis office, for up to 6 weeks a year.
REFLECTION DAYS â Two additional days of paid leave to step away from your usual dayâtoâday work and create time to focus on your wellâbeing and selfâcare.
HELP@HAND BENEFITS 24/7 helpline to support you on a personal and professional level. Access to remote GPs, mental health support and CBT. Wellâbeing content and lifestyle coaching.
FAMILY FRIENDLY POLICIES â We provide 26 weeks of full pay for the following family milestones: Maternity, Adoption, Surrogacy and Shared Parental Leave.
HYBRID WORKING, BANK HOLIDAY SWAP & BIRTHDAY DAY OFF â You are entitled to an additional day off for your birthday.
AGENCY DISCOUNTS , onsite gym, and discount in our PublicisâOwned Pub â \âThe Pregnant Man\â
Full details of our benefits will be shared when you join us!
Publicis Groupe operates a hybrid working pattern with fullâtime employees being officeâbased three days during the working week.
We are supportive of all candidates and are committed to providing a fair assessment process. If you have any circumstances (such as neurodiversity, physical or mental impairments or a medical condition) that may affect your assessment, please inform your Talent Acquisition Partner. We will discuss possible adjustments to ensure fairness. Rest assured, disclosing this information will not impact your treatment in our process.
Please make sure you check out the Publicis Career Page which showcases our Inclusive Benefits and our EAGs (Employee Action Groups).
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Data Science Lead employer: Publicis Groupe UK
Contact Detail:
Publicis Groupe UK Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Data Science Lead
â¨Tip Number 1
Familiarise yourself with the latest trends in causal inference and conformal prediction. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and expertise in these areas.
â¨Tip Number 2
Network with current or former employees of Digitas on platforms like LinkedIn. Engaging in conversations about their experiences can provide you with valuable insights into the company culture and expectations for the Data Science Lead role.
â¨Tip Number 3
Prepare to showcase your problem-solving skills by thinking of real-world examples where you've applied statistical methods to drive business decisions. Be ready to explain your thought process clearly, as communication is key in this role.
â¨Tip Number 4
Research Digitas' clients and projects to understand their business needs. Tailoring your discussion points to how your skills can specifically benefit their clients will make you stand out as a candidate who is genuinely interested in contributing to their success.
We think you need these skills to ace Data Science Lead
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly focusing on statistical methods, experimental design, and causal inference. Use specific examples that demonstrate your expertise in Python or R.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how it aligns with Digitas' mission of creating connections. Mention specific projects where you've applied statistical methods to drive business decisions.
Showcase Your Communication Skills: Since the role requires presenting complex ideas to non-technical audiences, include examples in your application that demonstrate your ability to communicate effectively. This could be through past presentations or collaborative projects.
Highlight Relevant Qualifications: Ensure you clearly state your advanced degree and any certifications related to data science. Emphasise your hands-on experience with statistical methods and any familiarity with causal inference frameworks.
How to prepare for a job interview at Publicis Groupe UK
â¨Showcase Your Statistical Expertise
Make sure to highlight your advanced degree and any relevant experience in applying statistical methods. Be prepared to discuss specific projects where you've designed experiments or used causal inference techniques.
â¨Demonstrate Your Technical Skills
Familiarise yourself with Python or R, especially the statistical and machine learning libraries. During the interview, be ready to explain how you've used these tools in past projects, particularly in developing conformal prediction models.
â¨Communicate Clearly
Since you'll need to present complex data insights to non-technical stakeholders, practice explaining your methodologies in simple terms. Use examples from your previous work to illustrate your points effectively.
â¨Prepare for Collaborative Scenarios
Expect questions about teamwork and collaboration. Think of instances where you've worked with product, engineering, or business teams to design experiments, and be ready to discuss how you contributed to those projects.
