Head of Insights & Decision Science - B2C
Who we are
We are an organisation that exists to drive progress. That's the “red thread” that connects everyone at The Economist Group (TEG). Our businesses share a devotion to innovation, independence and rigour in their fields of expertise. We empower people to understand and tackle the critical challenges and changes facing the world. Our analytical rigour, global expertise and evidence-based insights enable individuals and organisations to make sense of these shifts and chart a course through them.
We deliver analysis and insights in many formats to subscribers and clients in 170 countries through our four businesses, The Economist, Economist Impact, Economist Intelligence and Economist Education, which uphold our global reputation for excellence and integrity.
The role
The Head of Insights & Decision Science is a critical leadership role designed to transform the Insight function into a "trusted adviser" group. The primary purpose is to move beyond traditional insight towards providing bespoke diagnostic and prescriptive advice and insights that support high-stakes decision-making across The Economist Group’s B2C organisation.
This role, which manages both the analytics teams, is central to a wider strategy to make the Data, Research & Insight (DRI) function "fit for an AI-powered future," where human insight professionals focus on the "why" and "what next" while AI handles more routine data analysis. The Head of Insight & Decision Science will act as the senior insight leader in our B2C business - acting as the voice of the insight function in B2C executive fora and owning the roadmap and prioritisation for all B2C insight teams.
Measures of success
Success in this role will be measured through a combination of qualitative and quantitative indicators:
- Qualitative measures
- Trusted adviser status: The degree to which the role holder and their team are consulted proactively on complex strategic questions rather than being reactive "order-takers"
- Influence & relationship strength: The ability to build deep partnerships with business stakeholders to understand their core problems and influence decision-making.
- Insight narrative quality and impact: The effectiveness of storytelling and the creation of high-impact narratives that lead to clear business actions
- Focus on excellence & innovation: The degree which the team is regarded as a torch-bearer of excellence which sets and meets the highest standards in terms of quality, pace, innovation and expertise
- Quantitative measures
- Financial impact: Directly attributable net revenue impact (e.g., through experimentation, pricing, marketing and product insight driving decision-making) and operational cost savings
- Engagement impact: Improved speed of insight delivery and the degree of integration of data-driven insights into core business workflows
- Adoption: Level of engagement and usage of insight products and self-service tools both within the Insights & Decision Science team and across the organisation
Responsibilities
- Team leadership: Lead and manage a stakeholder-focussed multidisciplinary team of ~8-10 insight analysts across two teams
- Functional strategy: Drive the shift from descriptive/predictive reporting to diagnostic/prescriptive analysis using a mix of traditional and advanced techniques including causal inference, consumer research, econometrics, competitor intelligence, etc
- Roadmaps & priorities: Lead, coordinate and direct the overall team roadmap for the B2C business across insights, research data science and insight products to ensure that priorities and roadmaps are aligned, that the diverse skillsets of the team are effectively deployed and that insight from different sources are synthesised effectively
- Cross-functional collaboration: The B2C Research Manager will have a dotted reporting line into the Head of Insights & Decision Science and collaborate closely with the Insight Products Director and the Head of Data Science
- Consultancy & storytelling: Act as a senior consultant to the business, translating technical findings into compelling narratives and actionable recommendations.
- Data governance & quality: In collaboration with the Insight Products team, ensure high standards of data quality, availability, and observability to support decentralised insight creation
- Transformation & excellence: Create a culture of excellence, learning and innovation - in addition to a track record of developing outstanding talent pipelines and successors
- Innovation: Continuous and substantial process, technical and operating model innovation that delivers quantified KPI improvement and material commercial impact
Who you are
- Proven leadership: Extensive experience of leading high-performing insight or data science teams in complex, data-rich B2C environments.
- Commercial orientation: Pragmatic and commercial mindset that focuses on commercial urgency/materiality and that takes personal ownership and agency for commercial outcomes
- Transformation & excellence: Demonstrable record of creating a culture of excellence, learning and innovation in an insight, data science or research function - in addition to a track record of developing outstanding talent pipelines and successors
- Machine learning & AI: Experience of collaborating effectively with Data Science teams. Experience of upskilling analytics teams in AIML techniques and of embedding these approaches into their day-to-day toolkit is also essential. Experience with causal inference techniques is especially desirable.
- "T-Shaped" professionalism: A broad understanding of the data/insight landscape with deep, specialist expertise in at least one area (e.g. Analytics, or Data Science).
- Consultative mindset: A shift away from "order taking" toward a proactive, value-driven, and inquisitive approach to solving business problems.
- Technical proficiency: Experience in advanced techniques such as causal modelling, econometrics MMM, etc
- Influencing excellence: Exceptional storytelling and influencing skills, with the ability to build and sustain a "trusted adviser" relationship with C-suite stakeholders.
- Balancing pace & rigor: Able to demonstrate that they have been successful in increasing team impact through pragmatic trade-offs between pace and rigor. Able to demonstrate that they have been able to embed this approach in their team
- Leadership: Experience of managing "managers" and of leading diverse teams
- Mixed-methodology approach: Experience integrating market/competitor intelligence, user research, survey data and behavioral data to create cohesive, balanced and holistic narratives/strategies
- Domain knowledge: Strong data domain knowledge, ideally within a B2C, subscription-based, or media environment.
- (Desirable) AI Transformation: Experience in evolving data/insight functions to leverage AI for increased quality, velocity and effectiveness.
#LI-Hybrid
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.
What we offer
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.