(Immediate Start) Senior Data Scientist - Creative Optimization London, England...

Senior Data Scientist, Creative Optimization
Who we are:
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.
About the Creative Optimisation product:
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 enablespersonalization 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 servingtens of millions of adsand terabytes’ worth of media,everyday in real-time, across the globe.
About this role:
We are on the lookout for a Senior Data Scientist to join our team to co-develop astep-change feature: Algorithmic Content Opitmization (ACO). Our vision is to leaverage 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 asmall (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 thedeployment 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 spacewill 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 tosolvecutting-edgeproblems, anddrive measurable performance improvement for our clients. Not to mention, working with a team of supportive, seasoned deverlopers, product managers and data scientistswho 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 innovationsbased on your work

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 Learningas 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 aboutthe 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

Demonstrablestatistical 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

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

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