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Nonprofit Machine Learning Jobs in Arizona (NOW HIRING)

Hospice of the Valley

Senior Data & AI Engineer

Phoenix, AZ · On-site

$100K - $136K/yr

Join Arizona's largest, most prominent not-for-profit hospice, serving the valley since 1977 ... Analytics & Machine Learning * Build ML pipelines for risk stratification, cost/utilization ...

Hospice of the Valley

Senior Data & AI Engineer

Phoenix, AZ · Remote

$100K - $136K/yr

Join Arizona's largest, most prominent not-for-profit hospice, serving the valley since 1977 ... Analytics & Machine Learning * Build ML pipelines for risk stratification, cost/utilization ...

HCVT

Senior Data & Analytics Specialist

Phoenix, AZ · On-site

... Nonprofit Organizations, and Affordable Housing. We Live Our Core Values Our values guide us in our ... Define data models, standards, and architecture that support reporting, analytics, machine learning ...

New

HCVT

Senior Data & Analytics Specialist

Phoenix, AZ · Hybrid

... Nonprofit Organizations, and Affordable Housing. We Live Our Core Values Our values guide us in our ... Define data models, standards, and architecture that support reporting, analytics, machine learning ...

New

JP Morgan Chase

Business Insurance Manager

Tempe, AZ · On-site

Leverage an understanding of artificial intelligence and machine learning concepts to help inform ... We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their ...

nVent

Multi-Skilled Manufacturing Operator

Tempe, AZ

$16.75 - $20/hr

Rotating between multiple machines and production processes based on business needs * Using ... Through our nVent in Action matching program, we provide funds to nonprofit and educational ...

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Nonprofit Machine Learning information

What is a nonprofit machine learning professional?

A Nonprofit Machine Learning professional is someone who applies machine learning and data science techniques to help nonprofit organizations achieve their missions. This can include using predictive analytics to improve fundraising, optimize program delivery, or analyze the impact of initiatives. They often work with large datasets, develop algorithms, and collaborate with program staff to find data-driven solutions to social challenges. Their work helps nonprofits make more informed decisions and maximize their impact.

How does the role of a machine learning specialist in a nonprofit differ from similar roles in the private sector?

In a nonprofit setting, a Machine Learning Specialist often works with limited resources and must prioritize projects that directly support the organization's mission, such as optimizing donor outreach, improving program delivery, or analyzing social impact. Collaboration with program staff, fundraisers, and volunteers is common, requiring strong communication skills to translate technical insights into actionable strategies. Unlike the private sector, where profitability may be the primary focus, success in a nonprofit environment is measured by social outcomes and mission alignment. This role offers the opportunity to see the tangible impact of your work and can lead to leadership or strategic roles within the organization as you demonstrate value.

What are the key skills and qualifications needed to thrive as a nonprofit machine learning specialist, and why are they important?

To thrive as a Nonprofit Machine Learning Specialist, you need a strong background in data analysis, statistics, and machine learning, typically supported by a degree in computer science or a related field. Proficiency with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with donor management or CRM systems are highly valuable. Strong communication, problem-solving, and collaboration skills help translate technical solutions into meaningful impact for nonprofit missions. These abilities are crucial for leveraging data-driven insights to optimize resources, drive fundraising, and advance organizational goals.

What is the difference between Nonprofit Machine Learning vs Nonprofit Data Analyst?

AspectNonprofit Machine LearningNonprofit Data Analyst
Required SkillsMachine learning algorithms, programming (Python, R), statistical modelingData visualization, statistical analysis, Excel, SQL
Work EnvironmentResearch-focused, technical teams, data science projectsReporting, data interpretation, stakeholder communication
Employer & Industry UsageTech-driven nonprofits, research institutionsCharities, advocacy groups, social service agencies

Nonprofit Machine Learning roles focus on developing predictive models and advanced algorithms, requiring programming and statistical skills. Nonprofit Data Analysts primarily interpret and visualize data to inform decisions. While both roles support nonprofit missions, Machine Learning positions are more technical and research-oriented, whereas Data Analysts focus on data reporting and communication.

What are popular job titles related to Nonprofit Machine Learning jobs in Arizona?

For Nonprofit Machine Learning jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Nonprofit Machine Learning jobs in Arizona look for?

The top searched job categories for Nonprofit Machine Learning jobs in Arizona are:

What cities in Arizona are hiring for Nonprofit Machine Learning jobs?

Cities in Arizona with the most Nonprofit Machine Learning job openings:

Nonprofit Machine Learning jobs near you
Infographic showing various Nonprofit Machine Learning job openings in Arizona as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Senior Data & AI Engineer

Hospice of the Valley

Phoenix, AZ • On-site

$100K - $136K/yr

Full-time

PTO

Re-posted 26 days ago

Hospice Of The Valley (Arizona) rating

7.8

Company rating: 7.8 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

12th of 46 rated hospices

Job description

Join Arizona's largest, most prominent not-for-profit hospice, serving the valley since 1977.
Hospice of the Valley is a national leader in hospice care and has been serving the Phoenix metropolitan area since 1977. A mission-driven, not-for-profit organization, Hospice of the Valley employs compassionate, skilled professionals who are committed to excellence, enjoy teamwork, and contribute daily to our mission and culture of caring. Team members experience a friendly, supportive atmosphere, leadership support, autonomy, flexibility, and the privilege of doing meaningful, rewarding work.
Benefits:
  • Supportive work environment with a culture of caring for patients and one another.
  • Competitive wages and excellent benefit program.
  • Generous Paid Time Off.
  • Flexible schedules for work/life balance.

Position Profile
The Senior Data & AI Engineer will need to have deep hands‑on experience in Snowflake, Microsoft Fabric (incl. OneLake), and healthcare data ecosystems. The ideal candidate understands data modeling, data integration, and data transformation across structured and unstructured sources, and can build machine learning pipelines that operate on claims and clinical data. You'll design secure, scalable data platforms; map and normalize data across payers, providers, CMS datasets, EHR systems, and HIEs; and operationalize AI tools to drive measurable outcomes in cost, quality, and member/patient experience.
Responsibilities
Data Platform Engineering
  • Architect, implement, and optimize data solutions in Snowflake and Microsoft Fabric (incl. OneLake, Lakehouses, Warehouses, and Data Engineering pipelines).
  • Build robust ingestion frameworks for batch and streaming data (e.g., ADLS, EventHub, APIs, SFTP) with lineage and governance.
  • Manage data security, privacy, and compliance (HIPAA/PHI; role‑based access, masking, tokenization, de‑identification).

Data Modeling & Integration
  • Design conceptual/logical/physical models (normalized, dimensional/star, data vault where appropriate).
  • Implement data mapping and transformations for structured (claims, eligibility, provider, enrollment) and unstructured (clinical notes, PDFs) data.
  • Harmonize healthcare data using FHIR/HL7/C‑CDA, X12/EDI 837/835, NCPDP, and CMS standards; reconcile and link records across EHR and HIE sources.

Analytics & Machine Learning
  • Build ML pipelines for risk stratification, cost/utilization forecasting, fraud/waste/abuse detection, quality measure computation (e.g., HEDIS), and care gap identification.
  • Operationalize models with MLOps (experiment tracking, reproducibility, CI/CD, monitoring, drift detection).
  • Leverage LLMs/AI tools for data quality, entity resolution, summarization, and clinical insights-ensuring safety, bias checks, and auditability.

Governance & Observability
  • Implement data cataloging, lineage, and metadata (e.g., Microsoft Purview or equivalent).
  • Establish quality SLAs, validation rules, profiling, and automated anomaly detection.
  • Instrument pipelines for cost, performance, and reliability (e.g., Snowflake resource monitors, Fabric capacities).

Collaboration & Delivery
  • Work with product owners, clinicians, actuaries, and analytics teams to translate requirements into scalable solutions.
  • Produce clear documentation, data dictionaries, and mapping specs; mentor engineers and analysts.
  • Contribute to architectural roadmaps, reference patterns, and best practices across the enterprise.

Maintains and enhances professional skills.
Adheres to high standards of personal and professional conduct.
Minimum Qualifications
  • 8+ years in data engineering/analytics; 5+ years hands‑on with Snowflake (compute, storage, virtual warehouses, tasks, streams, Snowpipe, Time Travel, RBAC, row/column masking, data sharing, Dynamic Tables).
  • 2+ years with Microsoft Fabric (including OneLake, Lakehouses, Warehouses, Dataflows Gen2, Notebooks, Pipelines; capacity management).
  • Strong data modeling expertise (dimensional/star, 3NF, data vault; surrogate keys, SCD types, conformed dimensions).
  • Data integration & transformation proficiency: SQL (advanced), dbt or Fabric Dataflows/Power Query M, ADF/Synapse/Fabric Pipelines, Python for ETL/ELT.
  • Mapping from CMS data (e.g., Medicare datasets, claims/encounters), X12/EDI, FHIR/HL7, provider and eligibility.
  • Experience with structured (tables, CSV, Parquet) and unstructured (clinical notes, PDFs, blobs) data; NLP pipelines (optional but valued).
  • Machine learning: feature engineering, model training/evaluation, and deployment (e.g., scikit‑learn, PyTorch/TensorFlow, Fabric ML/Notebook, Azure ML); production monitoring.
  • Security & compliance: HIPAA, PHI handling, auditing, data residency, BAAs; practical access control in Snowflake/Fabric.
  • Strong communication; ability to author mapping specs, lineage docs, and present trade‑offs to technical and non‑technical stakeholders.

Preferred Qualifications
  • Interoperability: FHIR R4, HL7 v2, X12/EDI (837/835), NCPDP; experience with HIEs and EHR integrations (Epic, Cerner, etc.).
  • CMS & payer/provider data: Medicare fee‑for‑service, MA, Medicaid, CCW, APCD, and quality programs; risk adjustment (HCC), HEDIS measures.
  • MLOps & DevOps: MLflow, DVC, GitHub Actions/Azure DevOps, containerization (Docker), orchestration (Airflow, Fabric Pipelines, or ADF).
  • Governance: Microsoft Purview (catalog, lineage, classifications), data quality tools.
  • Visualization: Power BI and Fabric Direct Lake; semantic modeling and row‑level security.
  • Cloud: Azure (ADLS, Event Hub, Functions, Key Vault, Databricks), optional AWS/GCP exposure.
  • Certifications: Snowflake SnowPro Core/Advanced, Microsoft Certified (Azure Data Engineer Associate, Fabric Analytics Engineer).

Hospice of the Valley is an equal employment opportunity employer. EOE/M/F/D/V

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