Salesforce.com, Inc Data Scientist in Cambridge, Massachusetts
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Products and Technology
This role is only open to those who are current or prior Salesforce interns. All others who do not meet this criteria will not be considered.
Salesforce Commerce Cloud is the global leader of Cloud based (SaaS) E-Commerce solutions that enable the world’s premier retailers to maintain a robust online shopping presence. We empower our clients to improve their ROI by giving them the tools to effortlessly design and deploy seamless E-Commerce sites across traditional web, mobile, tablet and in-store applications. Commerce Cloud provides a highly scalable, integrated cloud platform that allows our clients to rapidly launch and manage multiple e-commerce stores, initiate unique marketing campaigns, and drive customer traffic across a global footprint. Our model serves for an environment of constant innovation which extends to our technology and internal company culture. Come join our team and over 500 retailers across more than 2000 sites around the world in seeing why we say at Commerce Cloud, “Move faster, Grow faster.”
We are looking for a top-notch data scientist to join the Commerce Cloud Einstein team at our office in Cambridge, Massachusetts. The Einstein product suite allows retailers and e-commerce companies to leverage real-time shopper data from across the globe to personalize customer interactions across the ecommerce ecosystem. We do this by capturing data from every customer touch point, mining behavioral signals using machine learning and advanced predictive algorithms and overlaying deep retail domain knowledge. Commerce Cloud Einstein technology enables merchandisers and marketers to drive substantial engagement and revenue.
The successful candidate will work with world-class database gurus, software engineers and data scientists on expanding the personalization and machine learning capabilities of the Einstein platform. If you have a passion for machine learning and experience with personalization and recommender systems, and a demonstrated history of delivering results, then we are very interested in talking to you.
Contribute to the research, design and construction of cutting-edge personalization systems that touch hundreds of millions of shoppers annually
Apply emerging AI technologies (e.g., deep learning, reinforcement learning ) to product, shopper and business-user data to take recommender systems and contextual personalization to the next level, as well as to devise new data products for use by digital commerce teams.
Rapidly iterate and develop algorithmic/model-based approaches, based on machine learning techniques, to retail prediction/targeting problems
Work closely with Engineering & Product teams to "productionize" winning approaches
Practical experience/ Knowledge in machine learning / deep learning / personalization / reinforcement learning
MS with 2+ years of experience or PhD in quantitative discipline with ideally internship experience / publications
Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets
Proficient in using Python (e.g., numpy, scipy, scikit-learn, tensorflow, theano, keras) to implement machine learning models and algorithms
Proficient in shell scripting, SQL and Unix/Linux command-line tools
Ability to summarize and clearly convey technical topics to non experts
Demonstrated experience with actually shipping code, getting data science into production
Public Cloud AWS/GCP/Azure/Alicloud experience
Some low level programming experience ( C/C++/Fortran/Java/Go etc.)
Experience with big data & emerging technologies (Cassandra/Spark/Flink/Vowpal )
You can explain how Factorization Machines get around the overfitting problem when using second-order interactions
You have presented a paper at RecSys / ICML / NIPS / CVPR (or a similar conference)
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