Overview
Are you passionate about changing the world through machine learning and location intelligence? Join Esri as we leverage the IoT revolution and explosive growth of location data to help organizations extract advanced intelligence, predict significant events, and automate work processes using AI and machine learning.
We're seeking a Data Scientist II who combines technical expertise with strong interpersonal skills to collaborate directly with customers, understand their unique challenges, and develop data-driven solutions that integrate seamlessly with GIS workflows. While prior GIS experience is not required, you'll work closely with GIS experts and gain valuable knowledge in spatial data analytics. This role offers growth toward increased technical ownership and customer-facing AI solution design.
We serve customers across diverse domains including natural resources, defense, commercial industries, public transportation, utilities, and governmental entities in over 160 countries.
Responsibilities
- 2+ years of hands-on machine learning experience, including building and evaluating supervised and unsupervised models (academic research or industry)
- Proficiency in Python for data science workflows, including data wrangling, exploratory analysis, and model development
- Solid foundation in statistics and the mathematical concepts underlying machine learning algorithms
- Experience with data extraction, transformation, and loading (ETL) across diverse data sources and systems
- Ability to produce clear data visualizations that communicate analytical results to stakeholders
- Strong communication skills, with demonstrated ability to explain technical concepts to non-technical audiences and collaborate across organizational boundaries
- Experience managing multiple concurrent projects with competing priorities
- Visa sponsorship is not available for this posting. Applicants must be authorized to work for any employer in the US.
- Bachelor's degree in mathematics, statistics, computer science, physics, or a related quantitative field
Recommended Qualifications
- Master's degree or PhD in mathematics, statistics, computer science, physics, or a related field
- Experience with spatial data, GIS concepts, or geospatial analytics, preferably using Esri software
- Familiarity with generative AI concepts, large language models, or agentic AI frameworks, including prompt design and evaluation of model outputs
- Experience with deep learning frameworks such as PyTorch or TensorFlow
- Proficiency with version control (Git) and collaborative development workflows
- Experience handling large-scale batch or streaming data with tools like Apache Spark
- Experience deploying data science or AI workloads on cloud platforms (AWS, Azure, or GCP).
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The Company
At Esri, diversity is more than just a word on a map. When employees of different experiences, perspectives, backgrounds, and cultures come together, we are more innovative and ultimately a better place to work. We believe in having a diverse workforce that is unified under our mission of creating positive global change. We understand that diversity, equity, and inclusion is not a destination but an ongoing process. We are committed to the continuation of learning, growing, and changing our workplace so every employee can contribute to their life's best work. Our commitment to these principles extends to the global communities we serve by creating positive change with GIS technology. For more information on Esri's Racial Equity and Social Justice initiatives, please visit our website here.
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 [email protected] 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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