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Senior Data Scientist - SMTS
•30 days ago
| Hours | Full-time, Part-time |
|---|---|
| Location | Cambridge, MA Cambridge, Massachusetts |
About this job
Salesforce Commerce Cloud (formerly Demandware) 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 1200 employees and over 400 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 Senior 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 Senior Data Scientist 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.
Pro tip: If you have attended RecSys, your resume will jump to the top of the heap :-)
Learn more about our Culture, Product, and Principles in these three videos - Company Culture , Product Overview & Operating Principles
Responsibilities
* 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, CNNs, RNNs) 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 team to "productionize" winning approaches
Qualifications Must-Have :
* Practical experience in machine learning or personalization
* MS or PhD in a quantitative discipline with 4+ years of experience or a BS in a quantitative discipline with 7+ years of experience
* Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets
* Knowledgeable about standard personalization approaches (i.e.matrix factorization techniques, neighborhood techniques)
* Proficient in using Python (e.g., numpy, scipy, scikit-learn, tensorflow, theano, keras) to implement machine learning models and algorithms
* Proficient in SQL, shell scripting and Unix/Linux command-line tools
Ideally:
* Demonstrated experience with actually shipping code, getting data science into production
* AWS experience
* Some low level programming experience ( C/C++/Fortran/Java/Go etc.)
* Experience with big data & emerging technologies (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 (or a similar conference)
Salesforce, the Customer Success Platform and world's #1 CRM, empowers companies to connect with their customers in a whole new way. The company was founded on three disruptive ideas: a new technology model in cloud computing, a pay-as-you-go business model, and a new integrated corporate philanthropy model. These founding principles have taken our company to great heights, including being named one of Forbes's "World's Most Innovative Company" five years in a row and one of Fortune's "100 Best Companies to Work For" eight years in a row. We are the fastest growing of the top 10 enterprise software companies, and this level of growth equals incredible opportunities to grow a career at Salesforce. Together, with our whole Ohana (Hawaiian for "family") made up of our employees, customers, partners and communities, we are working to improve the state of the world.
* LI-Y
We are looking for a top-notch Senior 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 Senior Data Scientist 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.
Pro tip: If you have attended RecSys, your resume will jump to the top of the heap :-)
Learn more about our Culture, Product, and Principles in these three videos - Company Culture , Product Overview & Operating Principles
Responsibilities
* 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, CNNs, RNNs) 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 team to "productionize" winning approaches
Qualifications Must-Have :
* Practical experience in machine learning or personalization
* MS or PhD in a quantitative discipline with 4+ years of experience or a BS in a quantitative discipline with 7+ years of experience
* Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets
* Knowledgeable about standard personalization approaches (i.e.matrix factorization techniques, neighborhood techniques)
* Proficient in using Python (e.g., numpy, scipy, scikit-learn, tensorflow, theano, keras) to implement machine learning models and algorithms
* Proficient in SQL, shell scripting and Unix/Linux command-line tools
Ideally:
* Demonstrated experience with actually shipping code, getting data science into production
* AWS experience
* Some low level programming experience ( C/C++/Fortran/Java/Go etc.)
* Experience with big data & emerging technologies (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 (or a similar conference)
Salesforce, the Customer Success Platform and world's #1 CRM, empowers companies to connect with their customers in a whole new way. The company was founded on three disruptive ideas: a new technology model in cloud computing, a pay-as-you-go business model, and a new integrated corporate philanthropy model. These founding principles have taken our company to great heights, including being named one of Forbes's "World's Most Innovative Company" five years in a row and one of Fortune's "100 Best Companies to Work For" eight years in a row. We are the fastest growing of the top 10 enterprise software companies, and this level of growth equals incredible opportunities to grow a career at Salesforce. Together, with our whole Ohana (Hawaiian for "family") made up of our employees, customers, partners and communities, we are working to improve the state of the world.
* LI-Y