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.
WHO WE ARE LOOKING FOR
The Choreograph Product & Engineering team is responsible for building the technology platform that powers the way we create audiences, forecast, price, and optimise cross-channel campaigns. The team consists of several specialist areas, including product management, project management, data science, technical design, and technical account management.
As a Senior Data Scientist in the Product & Engineering team, you’ll have the opportunity to design and develop innovative solutions and tackle complex challenges as part of a multi-disciplinary team whilst growing your skillset and supporting others to do the same.
We are hiring for multiple profiles within this role! Please help us identify the best opportunity for you by reviewing the profile details below. When applying, please highlight how your qualifications and experience align with at least one of the profiles. In addition to profile-specific skills, all candidates should also possess the qualifications outlined in the "Common Qualifications" section. We look forward to learning more about your expertise and how your unique skills can shape our teams’ success.
KEY RESPONSIBILITIES
- Collaborate with stakeholders to translate business needs into technical solutions. Create relevant materials, like dashboards and presentations to report back to our technical and non-technical audiences.
- Conduct data exploration and analysis, develop algorithms and ensure they are fit to go into production.
- Take ownership and responsibility for project prioritization and deliveries.
- Stay up to date with the latest advancements, and trends in data science and related technologies, and share knowledge with the wider team.
- Champion team standards and ways of working, contribute to a positive and productive environment where you support junior team members in their growth.
- Adhere to data governance and privacy policies to ensure compliance with relevant regulations and industry best practices.
COMMON QUALIFICATIONS FOR ALL PROFILES
- Bachelor's or master's degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Statistics, Physics, Economics or a related quantitative field
- At least 3 years of experience as a Data Scientist
- Excellent analytical skills and strong statistical knowledge, as well as experience in applying them to complex problems; good understanding of key ML frameworks
- Proficiency in Python and SQL
- Experience using cloud technologies (GCP preferred, but not essential)
- Full command of English – C1 level
- Self-motivation with the ability to make decisions in the absence of detailed instructions
- Ability to communicate complex analysis in a clear, precise, and actionable manner to collaborators from a variety of backgrounds
- Ability to lead effective collaboration with colleagues from data science, product and engineering
- Dedication to quality and passion for continuing to grow the skillsets of yourself and others
- A passion for empirical research and for answering hard questions with data.
- Nice to haves: Experience with Jira, scrum and git; commercial experience in software development; commercial ML Ops experience; understanding of media planning and/or experience in AdTech
PROFILE 1: PRE-FLIGHT MEDIA PLANNING
- Essential: Experience solving optimisation problems with Python
- Essential: Experience in creating mathematical models of complex systems (agent-based modelling a plus, but not essential)
- Essential: Experience as a leader: you should be able to take on most of the responsibility for the day-to-day execution of a project and/or guide a small team.
- Nice to have: Experience with MongoDB
PROFILE 2: IN-FLIGHT MEDIA OPTIMIZATION
- Essential: Hands-on experience in optimisation algorithms (or a related displicine). Please note:
- Whilst we’d consider candidates with relevant academic background, we’d prefer those with hands-on, commercial experience solving practical problems with real-world data.
- 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
- Experience of / exposure to model deployment and/or software development
- Nice to have: Hands-on experience in Airflow
PROFILE 3: IN-FLIGHT CREATIVE OPTIMIZATION
- Essential: 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
- Essential: Experience of / exposure to model deployment and/or software development
- Nice to have: Research degree (MRes or PhD) with a thesis on Reinforcement Learning or related discipline
- Nice to have: Knowledge / experience in Causal Inference
- Nice to have: Commercial experience in implementing and deployment RL or a similar personalisation system
PROFILE 4: COMMERCE MEDIA PLANNING & OPTIMIZATION
- Essential: Hands-on commercial experience in implementing time series / econometric modelling
- Essential: Hands-on (academic/commercial) experience on causal inference modelling.
- Essential: Experience of / exposure to model deployment and/or software development
