Product Analytics Manager (12 Month FTC)

CONDÉ NAST
London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Analytics Manager

Analytics Manager

Senior Customer Insights and Research Manager

Data & Analytics Strategy Manager

Product Manager- Electronics & Hardware

Product Manager (FemTech)

Condé Nast is a global media company producing the highest quality content with a footprint of more than 1 billion consumers in 32 territories through print, digital, video and social platforms. The company's portfolio includes many of the world's most respected and influential media properties including Vogue, Vanity Fair, Glamour, Self, GQ, The New Yorker, Condé Nast Traveler/Traveller, Allure, AD, Bon Appétit and Wired, among others.


Job Description


Location:
London, GB


Condé Nast is a global media company, home to iconic brands including Vogue, GQ, Glamour, AD, Vanity Fair and Wired, among many others. Our award-winning content reaches 84 million consumers in print, 367 million in digital and 379 million across social platforms, and generates more than 1 billion video views each month.


We are headquartered in London and New York, and operate in 31 markets worldwide, including China, France, Germany, India, Italy, Japan, Mexico & Latin America, Spain, Taiwan, the U.K. and the U.S., with local licence partners across the globe.


The Role


As Product Analytics Manager, your role is crucial to our mission of delivering an outstanding experience to our loyal and engaged readers and advertisers. You'll be working with business-wide stakeholders to deliver actionable insights, dashboards and experiments that help Conde' Nast achieve its ambitious product OKRs. You'll be collaborating closely with the Product, Engineering, and Data Science teams. It's a global role with immense responsibility and opportunity for impact across our brands.


We're looking for a strategic partner for the Product & Engineering teams, with experience creating analytical frameworks, collaborating with stakeholders, providing insights and data visualizations, providing data-driven guidance for product stakeholders, influencing and communicating across levels, and is an exceptional team player who is proactive, thorough, skeptical, detail-oriented, and highly organized. Your mission is to support Condé Nast product and engineering leaders in identifying trends, surfacing opportunities, evaluating the impact and trade-offs of product decisions between Conde's various lines of business, and support long-term strategic decisions that enhance organizational synergies.


What will you be doing?


  1. Provide full-stack analytical support focused on creating frameworks for measurement of analysis and actionable insights.
  2. Manage a team of product analysts.
  3. Initiate cross-pillar and matrixed analytics initiatives and strategies across the product and technology organization.
  4. Identify efficiencies, opportunities for expanded scope, and meeting global KPIs across the product and technology group.
  5. Scope and deliver a product analytics strategy that supports lines of revenue as well as broad narratives and cross-functional/pillar/enterprise analytics needs.
  6. Partner with relevant teams on the tooling & infrastructure (w/r/t software, platforms, data layers, experimentation) to support the organization.
  7. Scope and prioritize cross-pillar product analytics with data engineering, governance, privacy, data science, BI, TPM, privacy.
  8. Lead analytics, experimentation and tracking discussions, to ensure all required data and metrics are appropriately implemented for product and applied analytics initiatives.
  9. Produce analytical deep dives, focusing on actionable insights and recommendations, to address opportunities for enterprise product improvement.
  10. Drive engineering and data capabilities needed around dashboarding tools.


Who you are?


  1. Previous experience in a similar product analytics role, with a focus on innovative insights/deep dives, experimentation, visualization, stakeholder relationships and/or data storytelling.
  2. Previous experience managing a team of analysts.
  3. Exceptional critical thinking, problem-solving and analytical investigation skills.
  4. Strong business acumen, product thinking and understanding of customer behavior.
  5. Advanced SQL, Python, PySpark to extract, manipulate and model data.
  6. Working knowledge of visualization tools and methods.
  7. Proven ability to work with engineering and product senior leadership on OKRs and tracking implementation of new features and experiments.
  8. Excellent communication skills, including synthesis, presentation and storytelling.
  9. Bachelor's degree in quantitative field, STEM, social science, business, or humanities.
  10. Previous experience working with product data, with the ability to provide both big-picture product strategy and optimisation insights.
  11. Previous people management experience.
  12. Hands-on experience with a/b testing and/or multivariate testing tools and statistics, used to optimize user experiences.
  13. Deep understanding of human behavior, including behavioral science.
  14. Understanding of statistical models such as linear & logistic regression, clustering and segmentation, etc.
  15. Advanced data storytelling and visualization skills.
  16. Deep understanding of database technologies, specifically relational databases, data warehousing, or other database query tools and languages.
  17. Advanced data modeling skills and basic knowledge of analytics engineering processes and tools.


What benefits do we offer?


  1. 25 days holiday and extra days of annual leave for life events.
  2. Hybrid working and core hours.
  3. Competitive pension scheme.
  4. Bupa Private Healthcare.
  5. Enhanced maternity leave and family leave.
  6. Season ticket loans.
  7. Cycle to work scheme.
  8. Employee Assistance programme.
  9. Bring your dog to work.
  10. A wide variety of wellness benefits including gym discounts.
  11. Discounts and Magazine Subscriptions.
  12. Employee Resource Groups to provide a platform for employees to identify shared objectives, exchange ideas, and work on community priorities for our global workforce.
  13. Condé Nast Learning Hub where you'll find all Condé Nast-developed learning courses and trainings, and over 16,000+ courses in seven local languages.


What happens next?


If you are interested in this opportunity, please apply below, and we will review your application as soon as possible. You can update your resume or upload a cover letter at any time by accessing your candidate profile.


Condé Nast is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, familial status and other legally protected characteristics.


Where will you be?


We value collaboration, and our team comes together in the office three days a week. Our Adelphi office spans three floors, offering amazing views of the Thames and easy access to the amenities of The Strand. We truly love working here!

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.