Data Scientist (AI)

TL;DR

Data Scientist (AI): Building and deploying predictive models to optimize media investments for clients, leveraging machine learning and statistical algorithms on Google technology stack. Focus on creating measurable, scalable analytical solutions and establishing MLOps processes.

Location: London, United Kingdom. This is a UK-based role and requires individuals to have the right to work in this location. The company operates a hybrid approach, with teams in the office around four days a week.

Company

hirify.global is WPP’s global data products and technology company, transforming marketing by building a fast, connected, AI-enabled data platform.

What you will do

• Create, manage, and improve models for measuring, optimizing, and activating media campaigns.
• Build industry-relevant predictive models.
• Document analytics projects for replication and scalability across clients.
• Develop content to demonstrate the performance and value of statistical and predictive models.
• Deliver robust mathematical analysis and produce campaign reports.
• Establish MLOps processes leveraging the GCP toolset.

Requirements

• Hands-on experience building machine learning models with Python.
• Education and background in machine learning, computer science, physics, applied mathematics, or statistics.
• Experience developing complex query structures with SQL and/or NoSQL.
• Hands-on experience with GCP’s AI capabilities, including BigQuery ML and Vertex AI.
• Hands-on experience with machine learning techniques (TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, Pandas, NLTK, Spark MLib) and understanding of deep learning techniques.
• Understanding of or experience in software engineering best practices, DevOps, and MLOps.

Nice to have

• Experience in Google Marketing Platform and the use of Ads Data Hub.
• Capabilities in data engineering, data modeling, and complex big data analysis.

Culture & Benefits

• Investment in employee growth and development within WPP Media and WPP networks.
• Access to employee resource groups and frequent in-office events.
• Competitive medical, group retirement plans, vision, and dental insurance.
• Significant paid time off and employee mental health awareness days.
• Hybrid work approach with teams in the office around four days a week.