Principal Data Scientist - Search and Recommendation
As a Principal Data Scientist for Recommendations and Search, you will drive the quality of our Insights practice at Zalando. Leveraging recent advances in experimentation science, you develop innovative methods to support high-stake decision making and ensure that those methods become available to the right audience at Zalando.
For you to excel, you will need to demonstrate a blend of scientific depth and can-do attitude, as there is no shortage of opportunities where you can apply recent advances to practical applications and scale. Our corporate strategy requires us to not only understand traditional A/B experiments in depth but also explore and develop alternative designs and experimentation domains.
WHERE YOUR EXPERTISE IS NEEDED
Bring in your strong scientific experience to apply advanced experimentation methods in one of the most important algorithm-driven ecommerce domain
Support high stakes experiments and problems from design to execution and ensure decisions are made from robust insights
Research and develop principled reusable metrics and systems of metrics to deepen product and customer understanding
Set and own the processes to generate quality insights in the Recommendations and Search domains
Work closely with applied science leaders, product managers and other business stakeholders to bring our state of the art solutions to customers and to discover and identify new opportunities
WHAT WE ARE LOOKING FOR
PhD in Econometrics, Statistics, Mathematics, Physics, Operations Research or related field with at least 4 years of industry experience in applied Experimentation or Statistics
Expertise in 2 or more of the following areas:
Applied high dimensional statistics, variance reduction techniques
Long term, heterogeneous treatment effect estimation
Bayesian approaches to A/B testing
Advanced experiment designs: network experiments, bandit-based experimentation, interleaving, switchback experiments
Experience performing principled Causal Inferences and generating deep product insights based on these; from the problem analysis and data selection to their production deployment
Deep understanding of the theory behind the state-of-the-art methods in your domain as well as a broad overview of data science best practices in your field
Data intuition: extensive experience of working with large online datasets, ability to identify appropriate statistical modeling assumptions and approaches
Coding skills in Python and/or R as well as experience with common big data processing and manipulation tools such as Spark and SQL
Nice to have: experience with Cloud Computing frameworks (e.g., AWS), other programming languages such as Scala
PERKS AT WORK
Culture of trust, empowerment and constructive feedback, open source commitment, meetups, game nights, 70+ internal technical and fun guilds, knowledge sharing through tech talks, internal tech academy and blogs, product demos, parties & events.
Competitive salary, employee share shop, 40% Zalando shopping discount, discounts from external partners, centrally located offices, public transport discounts, municipality services, great IT equipment, flexible working times, additional holidays and volunteering time off, free beverages and fruits, diverse sports and health offerings.
Extensive onboarding, mentoring and personal development opportunities and an international team of experts.
Relocation assistance for internationals, PME family service and parent & child rooms* (*available in selected locations)
We celebrate diversity and are committed to building teams that represent a variety of backgrounds, perspectives and skills. All employment is decided on the basis of qualifications, merit and business need.
ABOUT ZALANDO
Zalando is Europe’s leading online platform for fashion, connecting customers, brands and partners across 23 markets. We drive digital solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to more than 52 million active customers through diverse skill-sets, interests and languages our teams choose to use.
