Senior Data Scientist - Creative Optimization

Description

About WPP Media

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About Choreograph: A Leading WPP Media Brand

Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.

Role Summary and Impact

The Creative Optimisation product is a DCO (Dynamic Creative Optimization) application that is built and maintained in-house at Choreograph, by the Optimization team.

The product enables personalization of creative content at scale, across multiple channels such as digital display, mobile apps, CTV, YouTube, video and social.

This is no start up. The application is already serving tens of millions of ads and terabytes’ worth of media, everyday in real-time, across the globe.

We are on the lookout for a Senior Data Scientist to join our team to co-develop a step-change feature: Algorithmic Content Opitmization (ACO). Our vision is to leverage data signals to algorithmically serve the most relevant creative to the right audience in the right moment that maximises performance, continuously.

The role will report to VP Data Science and be part of a small (but growing!) team of Data Scientists. The ideal candidate will have a background in Reinforcement Learning (or related disciplines), with hands-on cloud technology experience. Whilst commercial experience is highly desirable, given the deployment of RL at scale remains relatively nasant, we’re happy to consider candidates with academic research as well as commercial background.

The candidate though does have to be truly, technically competent. For the scale and complexity at which our product operates, off-the-shelf solutions are often not fit-for-purpose. The ideal candidate has to have the ability to customise source code, add in new features and code from scratch.

Whilst model deployment / software development experience is highly desirable, we do have a team of engineers to support so exposure in this space will be sufficient.

Culture-wise, we’re looking for a great team player who is passionate about applying Data Science techniques to solve complex problems and drive innovation.

In return, you will get the opportunity to solve cutting-edge problems and drive measurable performance improvement for our clients. Not to mention, working with a team of supportive, seasoned developers, product managers and data scientists who have successfully built and deployed scalable, global products.

Key Responsibilities:

• Develop and optimize the ACO algorithm(s) and related Data Science components for the product

• Design and contribute to the end-to-end machine learning pipeline from data collection, reprocessing to model training, simulation, evaluation, deployment and experimentation / testing

• Implement and interpret explainability frameworks to provide clear insights into model decisions, ensuring transparency and compliance with WPP standards

• Collaborate with stakeholders to identify business needs and translate these requirements into technical solutions that are scalable and impactful

• Conduct rigorous model testing and validation to ensure robustness and accuracy

• Prepare detailed documentation and reports that communicate complex model behaviours, predictions, and insights in a manner accessible to both technical and non-technical audiences

• Stay abreast of academic research and industry advancements in RL, plus AI/ML in general.

• Knowledge-share and support the wider team and Data Science community to drive innovations based on your work

Skills and Experience

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values:

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity.
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust .
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise .

Essential qualifications:

• Bachelor's or master's degree in Data Science, Computer Science, Engineering, Statistics, or a related quantitative field
• Hands-on (academic/commercial) experience in implementing Reinforcement Learning (or a related displicine). Please note:
• We use the term Reinforcement Learning as an umbrella term rather than a specialist term for state-dependent action set frameworks
• Completing a module / thesis on this topic as part of bachelor’s degree is not considered as sufficient academic experience. We’re primarily thinking about the experience of conducting an original piece of research as part of an MRes, PhD, fellowship, etc
• Proficiency in Python and SQL
• Experience of using Cloud technologies. GCP will be ideal, but other mainstream ones are fine as well
• Experience of / exposure to model deployment and/or software development
• Demonstrable statistical and machine learning knowledge
• Effective communication skills to work with different stakeholders / team members with varying degrees of knowledge in Data Science
• A collaborative team player

Highly Desirable qualifications:

• Research degree (MRes or PhD) with a thesis on Reinforcement Learning or related discipline
• Knowledge / experience in Causal Inference
• Commercial experience in implementing and deployment RL or a similar personalisation system
• Commercial experience in software development
• Commercial ML Ops experience

Life at WPP Media & Benefits

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.

WPP Media 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. 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.

Please note this is a UK based role and requires individuals to have the right to work in this location

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While we appreciate all applications received, only those candidates selected for an interview will be contacted.

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