Sr. Data Scientist - National Government

Are you passionate about changing the world through machine learning and location intelligence? If yes, then it's the right time to join our team because we are about to do so! With the IoT revolution, the consumerization of mapping and location data growing exponentially day after day, location is becoming extremely important to more and more people. We want to enable organizations and businesses to go beyond basic visualization and analytics of such massive data to the realm of being two or three steps ahead of the game by extracting advanced levels of intelligence from it, predicting important events, and automating significant proportions of their work through AI and machine learning.

We are looking for an entrepreneurial, collaborative person with strong hands-on experience and solid track record with statistical analysis, machine learning, predictive analytics, software engineering, and passion for location to help us on our mission to build world class predictive location analytics solutions for our customers in + countries.

Responsibilities

• Consult closely with customers to understand their needs
• Develop and pitch data science solutions by mapping business problems to machine learning or other advanced analytics approaches
• Build high-quality analytics systems that solve our customers' business problems using techniques from data mining, statistics, and machine learning
• Write clean, collaborative, and version-controlled code to process big data and streaming data from a variety of sources and types
• Perform feature engineering, model selection, and hyperparameter optimization to yield high predictive accuracy and deploy the model to production in a cloud, on-premises, or hybrid environment
• Implement best practices and patterns for geospatial machine learning and develop reusable technical components for demonstrations and rapid prototyping
• Keep up to date with the latest technology trends in machine and deep learning and incorporate them in project delivery

Requirements

• 5+ years of experience with Python in data science and deep learning
• Experience in building and optimizing supervised and unsupervised machine learning models including deep learning and various other modern data science techniques
• A fundamental understanding of mathematical and machine learning concepts such as calculus, back propagation, ReLU, Bayes theorem, Random Forests, time series analysis, and more
• Experience with applied statistics concepts
• Experience developing software collaboratively in Python using version control
• Ability to perform data extraction, transformation, loading from multiple sources and sinks
• Ability to produce data visualizations using tools such as matplotlib
• Self-motivated, life-long learner
• Strong communication skills, including to non-technical audiences
• Bachelor's degree in mathematics, statistics, computer science, physics or a similar field

Recommended Qualifications

• Familiarity with one or more of the following: Git, Pytorch, Tensorflow, CUDA / GPU programming
• Experience handling massive batch / streaming data using big data tools, such as Apache Spark
• Experience interacting with AWS, Azure, or other cloud service
• Experience building reinforcement learning models
• Experience with spatial and GIS concepts, preferably using Esri software
• Master's degree in mathematics, statistics, computer science, physics or a similar field

If you don't meet all of the preferred qualifications for this position, we encourage you to still apply!

Esri is an equal opportunity employer (EOE) and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need reasonable accommodation for any part of the employment process, please email and let us know the nature of your request and your contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this e-mail address.

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