The Economist Group - Head of Data Science
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Requirements
• Proven Leadership: A track record of building and raising standards within high-performance data science teams, with a demonstrable focus on talent development. • Technical Innovation with ROI: A proven record of delivering technical innovations that have resulted in quantifiable and material commercial benefits. • Curiosity with Purpose: A restless intellect that is constantly seeking to grow their skills and knowledge and, crucially, an operational and practical mindset that finds ways to apply that knowledge to deliver commercial benefits • Decision Science & Causal Inference: Deep expertise in causal inference, forecasting, and simulation techniques used to support business decision-making and to develop commercial and product strategy • Engineering Excellence: Strong experience in MLOps, model architecture, and delivering models at scale using AWS/Sagemaker. • Modern AI Stack: Hands-on experience with NLP, neural networks, transformer architectures, causal inference and the application of Generative AI in the AIML lifecycle. • Commercial Agency: An "owner's mindset" with the bravery to find and fix problems proactively and a focus on opportunity over risk. • Subscription/Journalistic Context: Experience in a premium news or subscription-based environment, understanding the specific challenges of content-based engagement. • Activation Platforms: Familiarity with activation via CDPs (e.g. Salesforce, Airship, Blueconic) and product analytics tools (e.g. Amplitude). • AI Transformation: Experience in evolving a traditional analytics function into an AI-forward team that leverages "full-stack" capabilities. • AI Transformation: • Working Arrangements • The majority of our roles operate on a hybrid working pattern, with 3+ days office attendance required. • AI usage for your application • We are an innovative organisation that encourages the use of technology. We recognise that candidates may utilise AI tools to support with their job application process. However, it is essential that all information you provide truthfully and accurately reflects your own experience, skills, and qualifications.
Responsibilities
• Team Leadership & Talent Nurturing: Lead, mentor, and develop a high-performance team of ~6 Data Scientists. You will be accountable for their technical growth and for maintaining a "T-shaped" culture that combines both broad and deep technical/business expertise. • Technical Standards & MLOps: Own the technical architecture and MLOps lifecycle for data science. In collaboration with the Data Engineering and AI Platform teams, you will drive excellence and pace in the build, deployment, testing, and monitoring of models using Amazon Sagemaker [and occasionally Snowflake] • Causal Inference & Decision Science: Lead the development of advanced causal models (e.g., Media Mix Modelling, retention drivers, and simulation models) to move the business from descriptive "what happened" to prescriptive ‘what next” and "what if" insights. • Personalisation Strategy & Activation: Oversee the Personalisation Analysts in their close collaboration with Marketing and Product teams to identify and execute opportunities using our CDP and activation platforms (Salesforce, Airship, Blueconic and Amplitude). • NLP & Generative AI Innovation: Leverage NLP and transformer architectures to enhance content tagging and use Generative AI to supercharge internal AIML workflows, including model testing and documentation. • Stakeholder Consultancy: Act as a senior technical consultant to executive fora, translating complex technical findings into compelling, actionable narratives. • Democratising AI & ML: Driving adoption of AI & ML techniques and tools in the wider Data, Research & Insight team and in the wider business • CANDIDATE PROFILE • CANDIDATE PROFILE
Benefits
• Our benefits package is designed to support your wellbeing, growth, and work-life balance. It includes a highly competitive pension or 401(k) plan, private health insurance, and 24/7 access to counselling and wellbeing resources through our Employee Assistance Program. • We also offer a range of lifestyle benefits, including our Work From Anywhere program, which allows you to work from any location where you have the legal right to do so for up to 25 days per year. In addition, we provide generous annual and parental leave, as well as dedicated days off for volunteering and even for moving home. • You will also be given free access to all The Economist content, including an online subscription, our range of apps, podcasts and more.
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