Position Details

DATA SCIENTISTS / MACHINE LEARNING ENGINEERS

Company: ESRI Positions: Data Scientists / Machine Learning Engineers (5 positions total, mid to Sr. Level) Employment Type: Direct Hire Compensation: ~130-190k + excellent benefits (see below) Visas: transfers can be considered Potential Locations: Redlands, CA 92373, Sacramento, CA 95814, Vienna, VA 22182, Broomfield, CO 80021, San Antonio, TX 78232, Chesterbrook, Eagan, MN 55121, Charlotte, NC 28226, Olympia, WA 98501, St. Charles, MO 63301, Middleton, MA 01949, possibly New York, NY 10001, possibly Richardson, TX 75080 Relocation Assistance: relocation assistance is available Travel: ~20-30% Nationwide Travel Summary: Machine learning is the top focus of almost every technology company--from the Silicon Valley to New York to around the world. What makes this type of technology so powerful? Context. Focusing on the where allows us to make sense of our businesses, lives, and world, whether that’s through automating portions of workflows to save companies millions of dollars or predicting life-altering events. We are looking for talented machine learning engineers to help build industry-leading predictive geospatial solutions for our customers in 160+ countries. We need a data scientist who is an individually driven, passionate professional to help us create machine learning best practices, not only within Esri but also for the broader GIS community. This game-changing opportunity requires someone with strong hands-on, proven experience with statistical analysis, machine learning, predictive analytics, and software engineering. If you are passionate about changing the world, literally, through machine learning you are in the right place. Where will you leave your mark? Required Skills/Experience: • Strong Machine Learning experience, some of which is within established technical organizations • Deep understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. • Experience in at least one of these toolkits: R, Weka, SciKitl-learn, MATLAB • Familiarity with machine learning frameworks/libraries/packages/APIs (e.g., Theano, Spark MLlib, H2O, TensorFlow, PyTorch, etc.) • Proven experience in ETL, data processing, transformation, cleaning, and data warehousing techniques • Experience with applied statistics skills, such as distributions, statistical testing, and regression • Experience with widely used probability methods (conditional probability, Bayes rule, likelihood, independence, etc.) • Experience with time series analysis • Experience with data visualization techniques and tools (e.g., ggPlot2) • Good software engineering background (OOP, data structures, algorithms, computability, and complexity) • Excellent conversation and communication skills – able to present on research and tools • Bachelor’s in a relevant quantitative field, such as statistics, operations research, or computer science, depending on position level (master's or PhD preferred) • Passionate, Innovative, and Motivated Desired Skills/Experience: • Experience training a deep Neural Net • Experience with Convolutional Neural Networks (CNN) • Proven understanding of multivariable calculus and linear algebra • Experience dealing with massive data sets, using big data tools (Hadoop HDFS, MapReduce, Accumulo, Presto, MongoDB, Cassandra, HBase, R, Mahout, Pig, and Hive, DC/OS) • Hands-on experience and expertise with cloud computing services (AWS, Azure, etc.) Responsibilities: • Apply data mining and machine learning techniques, perform statistical analysis, and build high-quality prediction systems that solve our customers' business problems • Explore, interpret, and analyze datasets for patterns of interest • Work closely with various teams to understand our customers’ needs, eventually crafting and pitching machine learning use cases to them • Model business problems to machine learning ones, map business data to dependent and independent features, perform proper feature engineering, iterate with different predictive models, and conduct hyper parameter optimization to yield highest prediction accuracy to deploy the model to production • Help build the data science and machine learning capability inside Esri by developing best practices and patterns for geospatial machine learning, developing reusable technical components for demos and POCs and identifying and helping establish the needed technology stack and infrastructure • Keep up to date with latest technology trends in machine and deep learning and quickly learn about new frameworks/techniques to be used in projects delivery Company Info: • Our passion for improving quality of life through geography is at the heart of everything we do. Esri’s geographic information system (GIS) technology inspires and enables governments, universities, and businesses worldwide to save money, lives, and our environment through a deeper understanding of the changing world around them. Carefully managed growth and zero debt give Esri stability that is uncommon in today's volatile business world. • Privately held, in business almost 50 years, profitable, with zero debt (extremely stable) • Over 50% of market share in the GIS industry • 350,000 clients • 3,100 employees • 10 US offices (corporate office in Redlands, CA) • 80 distributors worldwide • 1,800+ partners (we collaborate with major technology leaders: Amazon Web Services, Citrix, IBM, Microsoft, Oracle, SAP, SAS…) Benefits: • Medical, dental, vision (totally paid for employee and dependent) • Life Insurance – paid • Matched 401k • Profit Sharing into 401k • Holidays, Vacation, and Sick Time • Tuition Assistance

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