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Machine Learning Geospatial Jobs in New York (NOW HIRING)

T-Mobile

Senior Applied Scientist

New York, NY · On-site

$116K - $210K/yr

Experience operating production machine learning and data systems in cloud and containerized environments. * Experience in AdTech and GIS or geospatial data processing is a plus. * At least 18 years ...

NBCUniversal

Senior GIS Developer

Manhattan, NY

In this role, you will contribute to driving geospatial data and tooling needs for a large-scale ... Coordinate with AI/ML team to provide diverse data for developing new machine learning algorithms ...

NBCUniversal

Staff GIS Developer

Manhattan, NY · On-site

In this role, you will drive geospatial data and tooling needs for a large-scale project. You will ... Coordinate with AI/ML team to provide diverse data for developing new machine learning algorithms ...

NBCUniversal

Senior GIS Developer

Manhattan, NY · On-site

In this role, you will contribute to driving geospatial data and tooling needs for a large-scale ... Coordinate with AI/ML team to provide diverse data for developing new machine learning algorithms ...

NBCUniversal

Staff GIS Developer

Manhattan, NY

In this role, you will drive geospatial data and tooling needs for a large-scale project. You will ... Coordinate with AI/ML team to provide diverse data for developing new machine learning algorithms ...

NBCUniversal

Staff GIS Developer

Manhattan, NY · On-site

In this role, you will drive geospatial data and tooling needs for a large-scale project. You will ... Coordinate with AI/ML team to provide diverse data for developing new machine learning algorithms ...

NBCUniversal

Senior GIS Developer

Manhattan, NY · On-site

In this role, you will contribute to driving geospatial data and tooling needs for a large-scale ... Coordinate with AI/ML team to provide diverse data for developing new machine learning algorithms ...

Treeswift

Backend Engineer

Manhattan, NY · On-site

... geospatial queries via PostGIS, schema migrations, and data modeling for complex domain objects ... Treeswift utilizes robotic and machine learning technology to build forestry tools. Founded in 2020 ...

Neara

Data Scientist

New York, NY · On-site

$160K - $190K/yr

We use advanced machine learning to create engineering-grade, physics enabled digital twins of ... Geospatial data or power grid experience are a plus. * You have a strong intuition for data with ...

FreshDirect

Director of Engineering

Woodbridge, NJ · On-site

$160K - $190K/yr

Exposure to data science and machine learning applied to logistics or personalization. Nice to have ... Exposure to routing, geospatial, or timeslot/scheduling systems. * Familiarity with system ...

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All JobsMachine Learning Geospatial JobsMachine Learning Geospatial Jobs in New York

Machine Learning Geospatial information

What does a Machine Learning Geospatial professional do?

A Machine Learning Geospatial professional uses machine learning techniques to analyze and interpret geospatial data, such as satellite imagery, maps, and GPS data. Their work involves building and training models to detect patterns, make predictions, and solve spatial problems in fields like agriculture, urban planning, disaster response, and environmental monitoring. These professionals often collaborate with data scientists and GIS (Geographic Information Systems) specialists to extract actionable insights from large and complex geospatial datasets. Their skills are crucial for automating tasks such as image classification, land cover mapping, and object detection in geographic contexts.

What are the key skills and qualifications needed to thrive as a Machine Learning Geospatial professional?

To thrive as a Machine Learning Geospatial specialist, you need a strong background in machine learning, geospatial analysis, programming (Python, R), and a relevant degree in computer science, geography, or a related field. Familiarity with GIS software (e.g., ArcGIS, QGIS), remote sensing tools, and cloud platforms like Google Earth Engine or AWS is typically required. Analytical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with multidisciplinary teams. These skills and qualities are crucial for developing accurate geospatial models and delivering actionable insights from complex spatial data.

What are some common challenges faced by Machine Learning Geospatial professionals when integrating spatial data into predictive models?

Machine Learning Geospatial professionals often encounter challenges such as managing large and complex spatial datasets, ensuring data quality and consistency, and handling spatial autocorrelation that can bias model results. Additionally, integrating diverse data sources—like satellite imagery, sensor data, and GIS layers—requires advanced pre-processing and domain knowledge. Collaborating with GIS analysts and domain experts is usually essential to develop robust models that provide actionable insights.

What is the difference between Machine Learning Geospatial vs GIS Analyst?

AspectMachine Learning GeospatialGIS Analyst
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; knowledge of machine learning and geospatial dataBachelor's in Geography, GIS, or related fields; proficiency in GIS software
Work EnvironmentTech companies, data science teams, research institutionsGovernment agencies, urban planning, environmental firms
Industry UsageData-driven geospatial analysis, predictive modeling, AI applicationsMapping, spatial data management, spatial analysis

Machine Learning Geospatial professionals focus on applying machine learning techniques to analyze geospatial data, often working with large datasets and developing predictive models. GIS Analysts primarily handle spatial data management, mapping, and analysis using GIS software. While both roles work with geospatial data, Machine Learning Geospatial roles emphasize data science and AI, whereas GIS Analysts focus on spatial information management and visualization.

What are popular job titles related to Machine Learning Geospatial jobs in New York?

For Machine Learning Geospatial jobs in New York, the most frequently searched job titles are:

What job categories do people searching Machine Learning Geospatial jobs in New York look for?

The top searched job categories for Machine Learning Geospatial jobs in New York are:

What cities in New York are hiring for Machine Learning Geospatial jobs?

Cities in New York with the most Machine Learning Geospatial job openings:

Machine Learning Geospatial jobs near you

Applied AI/ML Modeling - Vice President

JPMorgan Chase & Co.

Manhattan, NY • On-site

$171K - $260K/yr

Full-time

Medical, Retirement

Re-posted 12 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

72nd of 171 rated banks

Job description


Our Branch Network Modeling team develops advanced analytics and machine learning solutions that inform high-impact decisions across physical location strategy and field workforce effectiveness.
As an Applied AI Modeling Vice President in Branch Network Modeling team, you will build advanced artificial intelligence (AI) and machine learning (ML) models that directly shape high-stakes decisions impacting Chase's branch network and the bankers who serve our customers. Your models will help optimize our branch network, using geospatial AI and graph-based models to determine where Chase should invest, grow, or reposition its physical footprint, or will empower our bankers in the field to serve our customers using techniques like reinforcement learning and behavioral science.
Job responsibilities
  • Develop and launch AI and ML models that solve complex, ambiguous business problems in Consumer Banking, spanning areas such as retail network optimization, investment optimization, resource allocation, and sales effectiveness.
  • Lead modeling engagements end-to-end, including interfacing with business, governance, UX, and technology stakeholders; articulating clear business use cases; delivering on project plans; and working with large, complex datasets - including geospatial, demographic, transactional, and behavioral data - to formulate testable business hypotheses.
  • Translate technical model outputs into clear, actionable recommendations for non-technical business partners in Real Estate, Finance, and Market Strategy.
  • Partner with governance teams to expedite fair and thorough model reviews, track performance metrics, and maintain adherence to regulatory compliance standards.

Required qualifications, capabilities, and skills
  • Advanced degree (master's or PhD) in a quantitative or spatial discipline such as Computer Science, Statistics, Machine Learning, Operations Research, Applied Mathematics, or Geography, or a related field.
  • 4+ years of hands-on, relevant industry experience in developing and deploying AI/ML models, including statistical modeling, ML, reinforcement learning, or optimization algorithms.
  • Proficient in Python with hands-on experience in ML and deep learning frameworks (TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit-Learn, Pandas). Strong working knowledge of Jupyter Notebook/Lab and cloud computing.
  • Deep expertise in at least one of the following, with meaningful exposure to at least one other:
    • Geospatial analytics, spatial statistics, or spatial optimization
    • Graph neural networks, network science, or graph-based optimization
    • Reinforcement learning, multi-armed bandits, or online/continuous learning
    • Behavioral modeling, adaptive intervention design, or human performance optimization

Preferred qualifications, capabilities, and skills
  • Hold a PhD in a relevant discipline.
  • Experience developing advanced AI or ML models in consumer finance, logistics, major retailers, or AI-native platforms.
  • Experience with at least one of the following: geospatial tools and libraries (e.g., GeoPandas, PySAL, H3, Esri/ArcGIS, Carto, Wherobots, QGIS), graph ML frameworks (e.g., PyTorch Geometric, DGL, NetworkX), RL libraries (e.g., RLlib, Stable Baselines, Vowpal Wabbit).
  • Familiarity with behavioral science concepts (e.g., nudge theory, decision theory) or experience building adaptive, continuous learning, or recommendation systems.
  • Experience with Databricks, Snowflake, or similar platforms.

About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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