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Gis Machine Learning Jobs in New Jersey (NOW HIRING)

Gis Machine Learning information

What is a GIS Machine Learning job?

GIS Machine Learning jobs involve applying machine learning techniques to geographic information systems (GIS) data to analyze spatial patterns, make predictions, and solve complex geospatial problems. Professionals in this field use algorithms and models to process location-based data, automate mapping tasks, and extract insights from satellite imagery or sensor data. These roles often require skills in programming, data analysis, and an understanding of both GIS principles and machine learning methodologies. GIS Machine Learning specialists can work in industries like urban planning, environmental monitoring, agriculture, and disaster management.

What are common challenges when integrating machine learning models with GIS data, and how can they be addressed?

One common challenge in GIS machine learning roles is handling the complexity and diversity of spatial data, which often comes in various formats and resolutions. Ensuring data quality and alignment is crucial, as inconsistencies can negatively impact model performance. Another challenge is computational efficiency, since spatial datasets can be very large. Collaboration with data engineers and GIS analysts is often necessary to preprocess data effectively and optimize workflows. Staying updated with advancements in geospatial libraries and cloud-based solutions can help address these challenges.

What are the key skills and qualifications needed to thrive as a GIS Machine Learning specialist, and why are they important?

To thrive as a GIS Machine Learning Specialist, you need expertise in geospatial analysis, machine learning algorithms, and a background in GIS-related fields, often supported by a relevant degree. Familiarity with tools like ArcGIS, QGIS, Python, R, and libraries such as scikit-learn and TensorFlow, as well as experience with spatial databases, is crucial. Strong problem-solving, critical thinking, and effective communication skills help translate complex data into actionable insights. These abilities enable professionals to develop innovative geospatial solutions and drive informed decision-making in diverse sectors.

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

AspectGis Machine LearningGIS Analyst
Required CredentialsBachelor's in GIS, Computer Science, or related; knowledge of machine learningBachelor's in Geography, GIS, or related; GIS certifications often preferred
Work EnvironmentData science teams, software development, research projectsUrban planning, environmental agencies, government offices
Employer & Industry UsageTech companies, research institutions, environmental firmsGovernment agencies, consulting firms, urban planning departments
Common Search & Comparison IntentUnderstanding technical skills and data modelingAnalyzing spatial data for projects and reports

Gis Machine Learning focuses on applying machine learning techniques to spatial data, often requiring programming and data science skills. In contrast, GIS Analysts primarily work with spatial data analysis, mapping, and reporting within various industries. While both roles involve GIS, Gis Machine Learning emphasizes advanced data modeling, whereas GIS Analysts focus on spatial data management and visualization.

What cities in New Jersey are hiring for Gis Machine Learning jobs?

Cities in New Jersey with the most Gis Machine Learning job openings:

Infographic showing various Gis Machine Learning job openings in New Jersey as of June 2026, with employment types broken down into 51% Full Time, 45% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Compliance - Quant Modeling Senior Associate Fair Lending

J.P. Morgan

Jersey City, NJ

Full-time

Medical, Retirement

Posted 18 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Job Responsibilities

  • Conduct research and develop innovative analytical and technology solutions to enhance fair lending risk analysis methodologies, improve process efficiency, and keep the fair lending compliance program aligned with industry and regulatory standards.

  • Leverage AI-enabled tools, generative AI, intelligent automation, and emerging technologies where appropriate to scale analytical capabilities, improve effectiveness, and reduce manual effort across fair lending processes.

  • Partner with Modeling, Technology, Data Science, and business teams to design, develop, and implement AI-enabled solutions, including intelligent agents, automated analytical workflows, and reusable tools that support fair lending analytics and model review processes. 

  • Evaluate, prototype, and deploy advanced analytical and AI-driven capabilities that enhance productivity, improve transparency, strengthen controls, and support scalable execution of compliance and risk-management activities.

  • Identify, request, and review relevant data to support ongoing and ad hoc fair lending analysis projects; identify potential gaps between data available for analysis and business policy requirements, such as underwriting attributes, and follow up with lines of business for resolution.

  • Develop and apply statistical models and techniques to evaluate potential fair lending disparities across lines of businesses; review and assess business policies, practices, and procedures to inform analytic strategies; develop quantitative and statistical models; perform independent analysis to assess fair lending risks; and make recommendations for fair lending testing.

  • Prepare and maintain model documentation, evaluate model performance, and ensure compliance with Model Risk Governance and Review standards. 

  • Support model review activities by assessing model methodologies, assumptions, segmentation approaches, performance metrics, and potential fair lending implications.

  • Prepare presentations and reports to communicate analytical results, solution designs, and innovation initiatives to technical and non-technical audiences; engage with stakeholders including OFL partner teams, lines of business (LOBs), Legal, Technology, Data Science, IT, and Model Governance.

  • Perform other related duties as assigned.

Required Qualifications, Capabilities and Skills

  • Graduate degree in a quantitative field, such as Statistics, Economics, Computer Science, Engineering, Data Science, Mathematics, or a related discipline.

  • 2+ years of experience in statistics, data science, business analytics, model review, or a related quantitative function.

  • Proficiency in Python, shell scripting, cloud computing platforms and tools (e.g., AWS, Spark, Git/Bitbucket, databricks) and database systems (e.g., Snowflake, Hadoop, Teradata, Hive).

  • Deep understanding of statistical concepts and methodologies, with the ability to apply them effectively to complex business and compliance questions.

  • Experience developing, implementing, and evaluating machine learning models with demonstrated ability to select appropriate modeling techniques, validate model performance, and interpret results to support business decision-making.

  • Experience applying data science, automation, artificial intelligence, machine learning, or advanced analytics techniques to solve business problems.

  • Strong critical thinking and analytical skills, with the ability to manage multiple projects in a fast-paced environment while maintaining a focus on quality.

  • Willingness to learn, adapt to changes, and work collaboratively as a team player.

  • Excellent verbal and written communication skills, with the ability to clearly present complex and sensitive issues to both technical and non-technical audiences.

Preferred Qualifications

  • Experience developing AI-enabled business solutions using generative AI, large language models (LLMs), retrieval-augmented generation (RAG), agentic systems, workflow automation platforms, or machine learning techniques.

  • Experience building proof-of-concepts and production-ready solutions that improve operational effectiveness, analytical capabilities, controls, or user experience.

  • Knowledge of cloud-based analytics, data engineering, or AI platforms is a plus. 

  • Experience with BI, GIS, or automation tools such as Tableau, ArcGIS, or Alteryx is a plus.

  • Experience in fair lending or responsible banking is a plus.

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

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.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

ABOUT THE TEAM

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.