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1 Day ago

Data Scientist

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Chennai, Tamil Nadu, India
Information Technology
Full-Time
Wayfair

Overview

Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their team's hybrid work schedule requirements.

Wayfair Data Science is the engine that powers an enterprise obsessed with data. The Wayfair websites generate over 100M clicks from the millions of customers that visit our sites every day to discover and purchase home goods. The Customer Tech Data Science team is focused on understanding and optimizing customer behavior on the website and mobile application as a key enabler for the company to move fast and iterate quickly on big business problems.

At their core, the Customer Tech Data Science team at Wayfair are strong in quantitative analysis, enjoy coding but also want to balance that with their interest in business and applying advanced modeling techniques. They think critically to tackle complex challenges, thrive in a fast-paced environment and are seeking a high-growth opportunity where they will have an immediate impact on day one. There are significant opportunities for new team members to emerge as leaders, taking on additional projects and responsibilities with strong performance.

What You’ll Do:

As a Data Scientist, you’ll play a critical role in uncovering insights that shape strategic decisions and improve business performance. You will explore data trends, diagnose gaps, and identify growth & innovation opportunities across Wayfair’s data. Your work will directly impact how the company understands performance and makes data-informed decisions.

  • Conduct in-depth analysis across large-scale datasets (clickstream, sales, product, logistics, and customer data) to uncover trends, gaps, and business opportunities.
  • Champion the use of emerging technologies - including GenAI and LLMs - to transform how we explore data and uncover insights, unlocking new ways to accelerate analysis, automate complex workflows, and make insights more accessible and actionable across the business.
  • Become a subject matter expert on key business metrics and customer behavior, ensuring accurate interpretation and analysis.
  • Drive innovation in business analysis by adopting and implementing new methodologies (e.g., key driver analysis, anomaly detection, forecasting, cohorting).
  • Establish robust KPI tracking and anomaly detection systems to ensure early identification of emerging issues and opportunities.
  • Collaborate with cross-functional partners—including Business Strategy, Product, and Engineering—to uncover actionable insights that drive growth and improve customer experience.
  • Design, run, and interpret A/B tests to make high-impact changes to the customer experience.
  • Build, automate, and maintain scalable dashboards and reports using tools like Looker, BigQuery (GBQ), SQL and Python to enable efficient and self-serve data access for stakeholders.
  • Develop optimized and maintainable code pipelines to transform multi-terabyte data into meaningful business insights and recommendations.

What You'll Need:

  • Bachelors in Computer Science, Computer Engineering, Analytics, Mathematics, Statistics, Information Systems, Economics, or other quantitative discipline; Masters preferred.
  • 3 - 5 years of work experience in a relevant field, such as analytics or data science.
  • Proficient knowledge of a statistical programming language such as Python, R, SAS, or SPSS.
  • Proficient knowledge of SQL (incl. Aggregate functions, joins, etc.).
  • Experience conducting quantitative analyses on large and complex data sets.
  • Experience in leveraging modeling algorithms to derive business insights.
  • Experience with experimental test design such as A/B testing.
  • Experience with data visualization software (e.g. Google Data Studio, Tableau, PowerBI); experience with Looker a plus.
  • Analytical, creative, and innovative approach to solving problems.
  • Strong written and verbal communication.
  • Ecommerce or retail analytics experience is a plus.
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