精选DS岗位 | Google、Grainger、Expedia Group公司岗位发布！

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【Expedia Group】

职位：Data Scientist II, Analytics

行业分类：Travel technology, primarily travel fare aggregators and travel metasearch engines

公司规模：15,200 (December 31, 2022 - incl. FTE & Vendors)

工作地点：United States - Washington - Seattle

• Bachelor's, Master’s or PhD in Mathematics, Science, Statistics, Economics degree; or equivalent related professional experience is applicable

• 2+ years experience in a similar analytical role

• Strong SQL skills; demonstrated experience of using R/PySpark/Python to structure, transform and visualize big data, and a willingness to learn new frameworks and languages required for the task

• A dynamic individual contributor who consistently applies - and often enhances - analytical resources, principles and playbooks to address business problems and realize opportunities

• Experience partnering with other teams and disciplines (Product, Engineering, Strategy, etc.) and collaborating with other analytics teams to deliver projects

• Good knowledge of developing, and delivering, presentations that help people understand the insight from sophisticated analytics

行业分类：Artificial intelligence, Advertising, Cloud computing, Computer software, Computer hardware, Internet

公司规模：139,995 (2021)

工作地点：Atlanta, GA, USA; Boulder, CO, USA

• Bachelor’s degree or equivalent practical experience.

• Experience designing data models, data warehouses, and using SQL and NoSQL database management systems along with data processing using traditional and distributed systems (e.g., Hadoop, Spark, Dataflow, Airflow).

• Experience in one or more object oriented programming languages (Java, C++, Python, etc.).

【Grainger】

职位：Data Scientist

行业分类：Industrial supply distribution

公司规模：24,200 (2021)

工作地点：LAKE FOREST, IL, US, 60045-5201 Hybrid, IL, US, N/A CHICAGO, IL, US, 60603-4013

职位要求：

• 2+ years of experience in analytics and data science roles or advanced degree 

• BS, MS, or PhD in a technical field such as Statistics, Mathematics, Data Science, Applied Analytics, Operations Research, Applied Science or Engineering 

• Proficient in usage of databases (e.g. Teradata, Snowflake, Oracle) and querying languages (e.g. SQL) 

• Experience with the following programming languages: Python, R, SPSS, or SAS 

• Experience working with very large structured and unstructured datasets 

• Experience with data visualization techniques 

• Experience with multi-variate linear regression, logistic regression, and time series modeling 

• Experience with statistical design of experiments, outlier detection methods, and statistical hypothesis testing 

• Experience translating analytical work into presentations (e.g. PowerPoint) suitable for non-technical audiences. 

• Experience with clustering and dimension reduction techniques 

• Experience with classification, gradient-boosting, and natural language processing algorithms 

• Experience using cloud-based machine learning resources such as those from AWS 

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