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Sr. Data Scientist - National Government

Esri Riyadh, Saudi Arabia Posted: 13 May 2025

Financial

  • Estimate: $90k - $120k*
  • Zero income tax location

Accessibility

  • Hybrid
  • Apply from abroad
  • Visa Provided

Requirements

  • Experience: Senior
  • English: Professional

Position

About the Job: 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 is growing exponentially, making location increasingly important. Our mission is to enable organizations and businesses to go beyond basic visualization and analytics to extract advanced levels of intelligence, predict important events, and automate significant proportions of their work through AI and machine learning.

We are looking for an entrepreneurial and collaborative individual with a strong hands-on experience and solid track record in statistical analysis, machine learning, predictive analytics, and software engineering. This role will focus on building world-class predictive location analytics solutions for our customers in over 160 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 data mining, statistics, and machine learning techniques.
  • Write clean, collaborative, and version-controlled code to process big data and streaming data from various sources and types.
  • Perform feature engineering, model selection, and hyperparameter optimization to yield high predictive accuracy, deploying the model to production in a cloud, on-premises, or hybrid environment.
  • Implement best practices for geospatial machine learning and develop reusable technical components for demonstrations and rapid prototyping.
  • Stay updated with the latest technology trends in machine and deep learning and incorporate them into 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 modern data science techniques.
  • Fundamental understanding of mathematical and machine learning concepts such as calculus, back propagation, and Bayes’ theorem.
  • Experience with applied statistics concepts and software development collaboratively in Python using version control.
  • Ability to perform data extraction, transformation, and loading from multiple sources and sinks.
  • Ability to produce data visualizations using tools such as matplotlib.
  • Self-motivated, lifelong learner with 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 Git, Pytorch, Tensorflow, and CUDA/GPU programming.
  • DevOps/MLOps experience using Docker/Kubernetes.
  • Experience handling massive batch/streaming data with big data tools like Apache Spark.
  • Experience interacting with AWS, Azure, or other cloud services.
  • Experience building reinforcement learning models.
  • Familiarity with spatial and GIS concepts, preferably using Esri software.
  • Master’s degree in mathematics, statistics, computer science, physics, or a related field is a plus.

Location: Riyadh, Riyadh, Saudi Arabia
Work Conditions: Hybrid, Full-time

Esri is an equal opportunity employer and encourages applications from all qualified candidates.

Apply now

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About Esri

Esri is the global market leader in geographic information system (GIS) software, location intelligence, and mapping. Since 1969, we have supported customers with geographic science and geospatial analytics, what we call The Science of Where. We take a geographic approach to problem-solving, brought to life by modern GIS technology.