Lead Applied Researcher

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

Looking for a company that inspires passion, courage and imagination, where you can be part of the team shaping the future of global commerce? Want to shape how millions of people buy, sell, connect, and share around the world? If you're interested in joining a purpose-driven community that is dedicated to creating an ambitious and inclusive environment, join eBay - a company you can be proud to be a part of.

Advertising is one of the fastest growing areas in ebay which in some ways, will define the future of ebay. Digital advertising as an industry is growing rapidly, and the landscape is shifting as ecommerce advertisers are finding better value with ecommerce companies like ebay. As they shift budget from the duopoly of google and facebook, it creates a huge opportunity for ebay. Advertising is also amplifying ebay’s ecommerce by providing a tool for our sellers to move inventory and for buyers, by surfacing high quality items.

As a leader of the Ads Seller Experience Applied Research team, you will be guiding a small team of very talented Applied Researchers. You bring in several years of experience in digital advertising, especially Cost-Per-Click model and have used a broad range of machine learning modelling techniques. This team focuses on building data / ML services for our advertiser sellers, to guide them ways to optimize for their ad budget and goals, for example by recommending the right inventory, keywords and Ads bid rate to apply for their campaigns, and eventually create campaigns automatically for advertisers. This is a relatively new area but with a very high business potential and need. It would allow you to work with massive amounts of data, and use a variety of data science techniques.

We are looking for passion for deploying to production reliable and efficient Machine Learning services at scale. You will collaborate with researchers to invent, design and implement end-to-end reliable, scalable, efficient production services in Python, Go, or similar languages (Java, Scala), using state-of-the-art big data and Machine Learning tools.

The ideal candidate will have a blend of science and engineering skills, proven track record of solving critical business problems through data science and strong analytical/quantitative and engineering skills. The candidate will be expected to have strong communication skills and to be capable of cross-group collaborations.

Come and help us blow away the boundaries of e-commerce through AI!

Responsibilities:

• Work with data scientists, engineers, and multi-functional teams to produce end-to-end production-ready solutions.

• Analyze Big Data to produce actionable insights

• Develop solutions for large scale problems in eBay

• Provide technical leadership and mentoring to other team members

• Translate business problems into Machine Learning problems

• Build quick prototypes and do preliminary explorations to decide on feasibility and direction

• Collaborate with other teams to build solutions across domains that work for advertisers

• Partner with senior scientists and architects with other domains teams like Search, AI Platforms

Requirements:

• MS in Computer Science, (PhD preferred) or equivalent experience.

• Experience in NLP, ML and statistical modeling.

• Experience with large data sets and related technologies, e.g., Hadoop and Spark. Knowledge of SQL is preferred.

• Excellent understanding of machine learning algorithms Strong programming skills in Python or Go (plus in one or more of Java, Scala, etc.).

• Experience building and deploying machine learning models in large scale production environments

• Experience with digital advertising domain, especially Cost Per Click Model, Click Fraud etc

• 7+ years of related work experience

• Strong analytical skills and data-driven decision-making

• Experience in solving problems using data science and building practical solutions

• Agility to adapt to emerging challenges and execute under ambiguity

• Strong communication skills.