Farfetch is a leading global marketplace for the luxury fashion industry. The Farfetch Marketplace connects customers in over 190 countries and territories with items from more than 50 countries and over 1,400 of the world’s best brands, boutiques, and department stores, delivering a truly unique shopping experience and access to the most extensive selection of luxury on a global marketplace.
TECHNOLOGY
We're on a mission to build end-to-end products and technology that powers the an incredible e-commerce experience for luxury customers everywhere, understanding the motivations and needs of our customers and partners, to designing and testing hypotheses, to creating industry-leading experiences for luxury customers.
PORTO
Our office is near Porto, in the north of Portugal, and is located in a vibrant business hub. It offers a dynamic and welcoming environment where our employees can connect and network with a large community of tech professionals.
THE ROLE (Porto or Lisbon based)
We power data-driven decision-making by providing statistical expertise, technical support, and actionable insights from experiments, ensuring Farfetch evolves through scientifically informed, rapid iteration. Our work spans the entire product ecosystem. We partner with Product teams to turn bold ideas into reality, guiding every stage from ideation to test design, analysis, and rollout decisions.
As a Data Analyst, you’ll fully engage within our experimentation platform, ensuring teams leverage robust user segmentation, hypothesis testing, and analytics to drive product evolution. You’ll bridge gaps between data engineering, product managers, and business owners—owning the quality of decisions derived from experiment results.
WHAT YOU'LL DO
Design and implement state-of-the-art methodologies for rigorous experiment design, analysis, and interpretationDevelop advanced analytical models and tools to enhance our experimentation platform's capabilitiesLead deep-dive analysis of A/B and multivariate tests, delivering actionable insights and strategic recommendationsResearch and implement cutting-edge methods to increase experimentation velocity and reliabilityContinuously improve our experimentation framework to support both rapid iteration and strategic testsPromote alignment across analytics, product, engineering, and operations teamsDefine and implement key success metrics to track product performance and business outcomesDevelop customer behavior models to optimize digital experiences and drive growth WHO YOU ARE
Expert in hierarchical Bayesian modelsFamiliar with econometric methods (IV regression, RDD)Knowledgeable of Python for statistical computing (Stan, TensorFlow Probability)Familiar with Cloud environments like GCP or AWSExperienced in BI tools such as Looker or Power BI.An individual with strong acumen in e-commerce, marketplace platforms or digital products REWARDS & BENEFITS
Health insurance for the whole family, flexible working environment and well-being support and toolsExtra days off, sabbatical program and days for you to give back for the communityTraining opportunities and free access to UdemyFlexible benefits program EQUAL OPPORTUNITIES STATEMENT
Farfetch is an equal opportunities employer ensuring that all applicants are treated equally and fairly throughout our recruitment process. We are determined that no applicant experiences discrimination on the basis of sex, race, ethnicity, religion or belief, disability, age, gender identity, ancestry, sexual orientation, veteran status, marriage and civil partnership, pregnancy and maternity, or any other basis prohibited by applicable law. SCAM DISCLAIMER
It has come to our attention that there may be fraudulent activities involving individuals or organizations falsely claiming to represent Farfetch in order to attract candidates to a SCAM. Please be aware that Farfetch does not conduct recruitment processes through messaging apps or any unofficial communication channels, other than our official careers website. Additionally, Farfetch will never ask candidates for any form of payment during the recruitment process.
