Job description
WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients, and communities.
Working at WPP means being part of a global network of more than 100,000 talented people dedicated to doing extraordinary work for our clients. We operate in over 100 countries, with corporate headquarters in New York, London and Singapore.
WPP is a world leader in marketing services, with deep AI, data and technology capabilities, global presence and unrivalled creative talent. Our clients include many of the biggest companies and advertisers in the world, including approximately 300 of the Fortune Global 500.
Our people are the key to our success. We’re committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow.
Why we’re hiring:
We are seeking a talented and driven Data Scientist to join our Customer Success tribe. In this pivotal role, you will be instrumental in transforming vast amounts of data into actionable business insights. You will work at the intersection of our Digital Pulse (data platform) and Voice of Customer (Survey Sense, Customer Insights) squads, designing and deploying high-impact machine learning models. Your work will directly influence product strategy, increase operational efficiency, and deliver significant customer value by uncovering the deep connections between user behavior and user sentiment.
What you’ll be doing:
1. End-to-End Model Development & Insight Generation:
Own the entire lifecycle of data science projects, from identifying business needs and proposing technical solutions to developing, validating, and deploying ML models into production.
Design and build models that leverage both quantitative platform data (from Digital Pulse) and qualitative user feedback (from Survey Sense & Customer Insights) to predict user behavior, satisfaction, and churn.
Apply a range of descriptive, predictive, and prescriptive modelling techniques to uncover hidden patterns, user segments, and key drivers of product success.
2. ML Operations & Model Maintenance:
Perform a critical role in supporting our ML solutions in production, ensuring the stability, continuity, and availability of all models.
Maintain, test, and continuously improve existing machine learning solutions to ensure they are capturing value and remain accurate.
Monitor model performance metrics in production to identify potential issues, detect root causes, and define resolution actions.
Collect and prioritize feedback from end-users and stakeholders to create a roadmap for model improvements.
3. Collaboration & Communication:
Translate complex business problems into clear, actionable data science projects with well-defined goals and success metrics.
Collaborate closely with Data Engineers, Product Managers, and User Researchers to design and deliver robust ML solutions that meet business needs.
Effectively communicate complex technical findings, model results, and strategic recommendations to both technical and non-technical audiences.
4. Innovation:
Continuously research and apply state-of-the-art techniques in Machine Learning, AI, NLP, and Gen AI to improve model performance and drive innovation.
Propose and develop new analytics solutions (“bottom-up innovations”) that create new opportunities for business value.
What you’ll need:
Experience: 6-8 years of hands-on experience applying data science and machine learning to solve complex business problems.
Education: A Bachelor’s degree in a technical field (e.g., Computer Science, Statistics, Mathematics, Data Science) is required. A Master’s degree or PhD in a relevant field is a strong plus.
Technical Proficiency:
Expert proficiency in Python and SQL is essential.
Proven experience with big data technologies like Spark.
Deep understanding of statistical methods and principles.
Modelling Expertise:
Proven experience with a variety of modelling techniques, including Time Series, Random Forests, Clustering, Neural Networks, NLP, and Generalized Linear Models.
Familiarity with Gen AI concepts and their practical applications is highly preferred.
MLOps: Experience with or a strong understanding of MLOps principles (implementing and maintaining models in production environments).
You’re Good At:
Translating ambiguous business problems into concrete data science projects.
Communicating complex findings to diverse stakeholders and influencing key decisions.
Collaborating effectively in a cross-functional, agile team environment.
Working in a fast-paced environment and taking ownership of project milestones.
Who you are:
You’re open : We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working.
You’re optimistic : We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected.
You’re extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day.
What we’ll give you:
Passionate, inspired people – We aim to create a culture in which people can do extraordinary work.
Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry.
Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge?
#LI-Onsite
We believe the best work happens when we’re together, fostering creativity, collaboration, and connection. That’s why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.
WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.
