Senior Machine Learning Scientist, Supplier Advertising Science

June 26

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Wayfair

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Wayfair is the destination for all things home: helping everyone, anywhere create their feeling of home$1. .$1

E-Commerce • Technology • Online Retail • Internet Marketing • Software Engineering

14172 - 14172

💰 $1.3G Post-IPO Debt on 2020-08

Description

• Provide technical leadership in the development of an automated and intelligent advertising system by advancing the state-of-the-art in machine learning techniques to support bidding and other optimizations. • Design, build, deploy and refine extensible, reusable, large-scale, and real-world platforms that optimize our ads experience. • Build robust monitoring, alerting, and edge-case handling mechanisms. • Collaborate closely and align with both our Ads and Search & Recommendations Product and Engineering partners to drive the integration of our smart bidding platform with the existing infrastructure and platforms at Wayfair. • Research new developments in advertising, sort and recommendations research and open-source packages, and incorporate them into our internal packages and systems. • Work cross-functionally with commercial stakeholders, engineers, analysts, and product managers to understand business problems or opportunities and develop appropriately scoped ML solutions • Promote a culture of machine learning and ML science excellence by participating in weekly research, learning, and development sharing sessions.

Requirements

• Advanced degree (Master or PhD) in Machine Learning, Computer Science, Engineering, Statistics, or a related quantitative field. • 3+ years (with PhD) or 5+ years (non-PhD) of experience in advanced machine learning and statistical modeling, including hands-on designing and building production models at scale. • Strong theoretical understanding and solid hands-on expertise deploying ML-based decision-making systems into production. • Familiarity with ML model development frameworks, ML orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Kubernetes, Docker, Python, and SQL.

Benefits

• Paid Holidays • Paid Time Off (PTO) • Full Health Benefits (Medical, Dental, Vision, HSA/FSA) • Life Insurance • Disability Protection (Short Term & Long Term Disability) • Global Wellbeing: Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships) • Mental Health Support (Global Mental Health, Global Wayhealthy Recordings) • Caregiver Services • 401K Matching (Employee Matching Program) • Tuition Reimbursement • Financial Health Education (Knowledge of Financial Education - KOFE) • Tax Advantaged Accounts • Family Planning Support • Parental Leave • Global Surrogacy & Adoption Policy • Rewards & Recognition • Global Employee Anniversary Awards • Paid Volunteer Work • Employee Discount • U.S. Bluebikes Membership • Global Pod Outings • Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments