Senior Geospatial Data Scientist

1w1 week ago

Esri

SA · Full-time · SAR 350,000 – SAR 550,000

About this role

Are you passionate about changing the world through machine learning and location intelligence? With the IoT revolution and consumerization of mapping data growing exponentially, location is becoming extremely important. We want to enable organizations to extract advanced intelligence, predict events, and automate work through AI.

We seek an entrepreneurial, collaborative person with hands-on experience in statistical analysis, machine learning, predictive analytics, software engineering, and passion for location. Help build world-class predictive location analytics solutions for customers in 160+ countries. Join our mission to go beyond basic visualization of massive data.

Consult closely with customers to understand needs and map business problems to machine learning approaches. Build high-quality analytics systems using data mining, statistics, and machine learning. Write clean, version-controlled code to process big and streaming data from various sources.

Perform feature engineering, model selection, hyperparameter optimization, and deploy models to production in cloud, on-premises, or hybrid environments. Implement best practices for geospatial machine learning and develop reusable components. Keep up with latest trends in machine and deep learning for 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
Strong communication skills, including to non-technical audiences

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 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