At eBay, you will be part of a purpose driven community dedicated to creating a bold and versatile work environment. In eBay Risk and Protections, you will be an integral member of an organization that inspires passion, courage and inventiveness - creating the future of global commerce and making an important, positive impact on millions of eBay sellers and shoppers around the world. Our focus is to ensure the integrity of our marketplace for buyers and sellers who transact with us every single day. The scope of our charter includes Risk Management Strategy, Policy, Decision Sciences, and Policy Operations.
We are looking for a highly talented and self-motivated data scientist to join our Decision Science team. Decision Science contains both data scientists and software engineers responsible for creating and implementing state of the art machine learning algorithms for fraud detection and risk assessment in support of Risk Management. The primary responsibility of this role is to assist in algorithm development inside of a high throughput, low latency, big data environment.
Primary Job Responsibilities
The senior data scientist will support the risk department, leveraging big data technologies to aggregate and structure data, perform statistical analysis, and build algorithmic solutions to reduce fraud, monitor our buyers and sellers, and intermediate Risk to improve the overall eBay experience. As a member of the decision science team, you will research and develop new methodologies and techniques to improve the overall effectiveness of risk management. Mine and analyze massive amounts of unique internal and external data to gain deep business knowledge and insight on customer activity and usage behaviors and their relationships with fraud, credit risks, and other types of behaviors. Acts as the technical owner of projects that may require significant customization of existing analytic tools, techniques, processes or development of new ones. Perform statistical data analysis and understanding, ensure data quality, and develop tracking and reporting systems to determine the effectiveness of models, rules, and other risk initiatives and programs. Design and create systems to structure, aggregate, and turn petabytes of messy information into statistically significant features for modeling purposes. Problem sets are focused around fraud and risk management to include models to prevent fraudsters from listing and monetizing on the platform, thwarting registration attacks, and risk scoring our customers. We are look for an individual contributor who can also take initiative to guide small groups in tactical projects and help coordinate cross-team effort, provide thought leadership within the broader decision science team, and be a mentor for junior scientists.
Required Skills and Experience:
Bachelor’s degree in a quantitative field: engineering, math, statistics etc. MS/PHD preferred
MS + 7, PHD + 4 years minimum
Experience in SQL, relational databases
Experience with Big Data technology: Hadoop framework: Hive, Spark, etc. a plus
Expertise in machine learning packages Python, R, SAS
Strong knowledge of 1 or more scripting and programming languages (Python, Java, Scala, etc.) Experience develop software packages is preferred. Hands-on experience with PyTorch or TensorFlow is preferred.
Background in a variety of machine learning techniques such as: GBM, logistic regression, clustering, deep learning, NLP, CV, graph algorithms, reinforcement learning, semi-supervised or unsupervised learning, anomaly detection
Strong understanding of statistics and experimentation
Strong analytical skills with good problem solving ability
Experience mentoring junior scientists
Strong presentation and communication skills and the ability to explain technical things to a non-technical audience.
Good listening skills
Ability to think strategically
Agility to adapt to emerging challenges and execute under ambiguity.
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