Machine Learning Jobs in Tempe, AZ

Lead design and execution of AI-enabled workforce management forecasting, capacity planning, and data pipelines for CX. Build governance, dashboards, and predictive models, partner cross-functionally, monitor real-time alerts (PagerDuty), and provide staffing and hiring recommendations to optimize contact center operations.

Develop and deploy predictive and descriptive models (including ML) across the customer lifecycle, perform deep-dive analytics, build BI to monitor program results, and partner with stakeholders to apply risk modeling and analytics to business problems.

Nine-week summer analyst program within Operations supporting processing, trade/asset support, reporting, transformation, and data management. Responsibilities include transaction processing, reconciliations, client lifecycle support, data analytics and reporting, risk reporting, process improvement, and creating Tableau dashboards. Program includes training, networking, and may lead to full-time roles.

Supports business decision-making through data analysis, predictive modeling, statistical and machine learning techniques, and presentation of insights. Interns will work across marketing, lending, indirect lending, and warranties while gaining hands-on experience throughout the data science lifecycle. The role is an 11-week, paid, on-site internship based in Tempe, Arizona, or Dallas, Texas, with no relocation assistance.

Leads prepaid debit card fraud risk management, including fraud strategy, controls, loss performance, trend monitoring, root-cause analysis, and mitigation. Manages and develops fraud analyst experts while partnering with product, operations, technology, compliance, payment networks, issuing banks, and regulators. Supports launches, audits, client proposals, escalations, and executive reporting. Promotes responsible use of AI, machine learning, analytics, visualization, and data storytelling to improve fraud outcomes.

Architect and implement finance solutions in Dynamics 365 Finance & Operations, optimizing core accounting processes, integrations, reporting, automation, and AI capabilities. Lead finance-related projects from requirements through deployment and support, advise finance leadership, support mergers and acquisitions, ensure data integrity and governance, and mentor functional analysts. Partner with technical, finance, analytics, and enterprise architecture teams to deliver scalable systems aligned with business goals.

Design, develop, and productionize machine learning and generative AI solutions; build conversational AI and cloud-based systems; troubleshoot and support production; lead deployments; mentor teams; drive end-to-end delivery and responsible AI practices.

Leads the design and transformation of Securities Lending operating models, workflows, technology capabilities, automation, and data solutions. Develops improvement roadmaps, future-state processes, governance, and performance frameworks; leads cross-functional projects and change adoption; evaluates industry and fintech trends; partners with Technology, Risk, Product, and Operations teams; and drives automation, analytics, risk reduction, and operational efficiency.

Develops and maintains profitable vehicle transportation lane pricing across automotive customer segments. Responsibilities include benchmarking rates, building pricing models and dashboards, auditing rate and billing data, supporting bids and contract pricing, forecasting margins, identifying revenue leakage, and recommending rate changes. The role partners with Sales, Operations, Finance, Data Science, and Engineering while governing rate structures, documenting methodologies, and improving pricing automation and data quality.

Develop and maintain enterprise GIS applications, geoprocessing workflows, mapping systems, integrations, and ArcGIS services. Automate GIS processes with Python and ArcGIS APIs; support upgrades, migrations, testing, monitoring, troubleshooting, and 24/7 on-call operations. Process drone imagery, point clouds, and 3D datasets, and apply GeoAI and machine learning to spatial analysis. Provide advanced technical support while collaborating across teams on security, governance, reliability, and platform improvements.

Classify patent applications using CPC and USPC systems, technical research, and automated tools. The role involves learning classification processes, evaluating applications across computer science and electrical engineering technologies, expanding technical expertise, and meeting production and quality standards independently while collaborating with a team.

Performs wafer-level semiconductor device characterization, reliability testing, and automated measurement development. Operates probe stations and parameter analyzers, develops Python-based instrument control and data-analysis workflows, validates data quality, troubleshoots integrated hardware and software systems, and applies statistics, AI, and machine learning to anomaly detection, test optimization, predictive maintenance, and reporting. Owns laboratory test systems, calibration, maintenance, compliance, scheduling, documentation, and user training while collaborating with engineering, facilities, vendors, and external partners.

Design and guide enterprise-scale, cloud-native solutions leveraging software engineering and AI. Provide technical leadership across SDLC, design mobile/cloud apps, integrate via APIs and data services, implement CI/CD and release/configuration practices, and architect end-to-end ML pipelines for cloud and edge deployment while aligning solutions with business objectives.

Seeking a Senior Cybersecurity Analyst for monitoring threats, responding to incidents, and utilizing AI/machine learning tools within SOC. Responsibilities include threat detection, incident analysis, and integration of Google SecOps tools.

Lead enterprise AI strategy, governance, and adoption; partner with business and technical leaders to prioritize use cases, measure value and risk, and guide secure, responsible implementation of AI solutions while managing and developing AI talent.

Lead end-to-end analytics for Flagship Client and Distribution: partner with stakeholders to frame problems, perform advanced analyses and machine learning, ensure data quality, develop recurring analytics products and executive visualizations, and mentor analysts to drive data-driven decisions.

Leads technology development for composite wind blade design, materials, manufacturing, tooling, and automation. Owns maturation from early research through production implementation, establishes technology roadmaps and stage-gate processes, and applies AI/ML to engineering and manufacturing challenges. Builds technical teams, manages budgets and partnerships, directs modeling and validation, supports production transitions, develops business cases, and protects intellectual property. The role collaborates globally with engineering, operations, quality, suppliers, customers, universities, and technology partners.

Lead the design and operations of an AI-driven Insider Threat Detection & Response program. Develop behavioral analytics, anomaly detection, and proactive threat-hunting; design detections for data exfiltration, privileged misuse, and account compromise; lead investigations and responses; partner with Legal, HR, Privacy, and Compliance; deliver executive risk assessments and playbooks.

Lead application and cloud security architecture for APIs, microservices, and AI/ML pipelines. Design secure access (OAuth/OpenID/JWT), threat modeling, SIEM/logging, incident response, risk management, and reusable security patterns. Collaborate across development, operations, and enterprise teams to implement zero-trust, secure DevOps practices, and regulatory-aligned security standards.

Lead simulation-driven development of power modules using multiphysics (electrical, thermal, mechanical) models, digital twins, AI-augmented optimization, and automation to accelerate SiC/GaN power-electronics design and reliability prediction while collaborating with global teams.

Develop and optimize predictive models for credit and risk, leveraging advanced machine learning techniques to improve accuracy and decision quality.

Lead the Forward Deployed AI Engineering team to build solutions, engage customers, and enhance cybersecurity with AI tools and data science.

Lead technical vision and architecture for enterprise ML platforms and MLOps. Design training, feature, serving, and observability systems; establish ML lifecycle and governance; solve complex cross-team engineering problems; mentor senior engineers; evaluate emerging AI technologies; drive cost optimization, compliance, and organizational alignment.

The Vice President of Data Science oversees AI-driven clinical insights and predictive modeling, leading a team to develop novel AI signatures from clinico-genomic data. Responsibilities include strategy execution, model governance, and collaborative efforts across multiple departments to enhance precision medicine.

Senior individual contributor responsible for leading pet/P&C insurance pricing model development (GLMs and ML), owning end-to-end projects, performing EDA and root-cause analysis, communicating results to stakeholders, and mentoring junior team members.