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Ai In Finance Jobs in Arizona (NOW HIRING)

... heavily in technology, automation, AI-enabled analytics, and scalable reporting capabilities. We are hiring a Junior Financial Analyst to support the company's financial planning, operational ...

... heavily in technology, automation, AI-enabled analytics, and scalable reporting capabilities. We are hiring a Junior Financial Analyst to support the company's financial planning, operational ...

... heavily in technology, automation, AI-enabled analytics, and scalable reporting capabilities. We are hiring a Junior Financial Analyst to support the company's financial planning, operational ...

AI Engineer

Phoenix, AZ · On-site

$110K - $125K/yr

... in financial services • Understanding of automated code build solutions for CI/CD Pipelines. • Full stack development • Strong interpersonal & problem-solving skills along with the ability to ...

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... At least 3 years of hands-on experience in business settings across finance, healthcare, consulting ...

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... At least 3 years of hands-on experience in business settings across finance, healthcare, consulting ...

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... At least 3 years of hands-on experience in business settings across finance, healthcare, consulting ...

AI Engineer III - Agentic AI

Phoenix, AZ · Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

... in financial services. We partner closely with product, design, and business teams to deliver ... The Role As an AI Engineer III - Agentic AI, you will be a hands-on builder contributing to the ...

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... At least 3 years of hands-on experience in business settings across finance, healthcare, consulting ...

Showing results 41-60

Ai In Finance information

See Arizona salary details

$23.3K

$86.3K

$126.3K

How much do ai in finance jobs pay per year?

As of Aug 18, 2026, the average yearly pay for ai in finance in Arizona is $86,322.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,900.00 and $101,600.00 per year, depending on experience, location, and employer.

What is AI in finance?

AI in finance refers to the use of artificial intelligence technologies and machine learning algorithms to automate, enhance, and optimize various financial services and processes. This includes applications such as fraud detection, algorithmic trading, credit risk assessment, customer service chatbots, and personalized financial advice. By leveraging large datasets and advanced analytics, AI can improve decision-making, reduce operational costs, and deliver more accurate and timely financial insights. Many financial institutions are increasingly adopting AI to stay competitive and comply with regulatory requirements.

What are the key skills and qualifications needed to thrive as an AI professional in finance?

To thrive as an AI professional in Finance, you need a strong background in data science, machine learning, quantitative analysis, and finance, often supported by degrees in computer science, mathematics, or finance. Familiarity with programming languages like Python or R, experience with AI/ML frameworks (such as TensorFlow or PyTorch), and understanding of financial systems or regulatory standards are typically required. Strong analytical thinking, attention to detail, and effective communication skills set top performers apart in this field. These skills are vital for developing robust AI solutions that drive financial insights, improve decision-making, and ensure regulatory compliance.

How do professionals in AI in finance typically collaborate with other departments within a financial institution?

Professionals working in AI in Finance often collaborate closely with teams such as risk management, compliance, and data engineering. They work together to define business requirements, ensure the quality and security of financial data, and interpret AI models’ results for practical decision-making. Effective communication is key, as AI specialists must translate complex technical findings into actionable insights for non-technical stakeholders. This collaborative environment fosters innovation and helps drive solutions that align with both regulatory standards and business goals.

What is the difference between Ai In Finance vs Data Analyst in Finance?

AspectAi In FinanceData Analyst in Finance
Required CredentialsDegree in Finance, Computer Science, or related fields; knowledge of AI and machine learningDegree in Finance, Statistics, or related fields; proficiency in data analysis tools
Work EnvironmentTech-driven finance teams, AI development labs, financial institutionsFinancial firms, banks, investment companies, data analysis departments
Employer & Industry UsageFinancial technology companies, banks integrating AI solutionsFinancial services firms analyzing market data, risk, and client information

Ai In Finance focuses on developing and implementing AI solutions within finance, requiring technical and financial expertise. Data Analysts in Finance interpret financial data to support decision-making. While both roles work with financial data, Ai In Finance emphasizes AI development, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Ai In Finance jobs in Arizona?

For Ai In Finance jobs in Arizona, the most frequently searched job titles are:

What cities in Arizona are hiring for Ai In Finance jobs?

Cities in Arizona with the most Ai In Finance job openings:

Infographic showing various Ai In Finance job openings in Arizona as of August 2026, with employment types broken down into 78% Full Time, 18% Part Time, 2% Temporary, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $86,322 per year, or $41.5 per hour.

Manager, Applied AI Strategy and Operations

Cloudera

Phoenix, AZ • On-site

Other

PTO

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Business Area:

Corp. Strategy

Seniority Level:

Mid-Senior level

Job Description:

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world's largest enterprises.

Job title: Manager, Applied AI Strategy and Operations

Job Purpose:

As a Manager, Applied AI Strategy and Operations within the Chief Business Officer and GM, Applied AI's organization, you will lead high-impact, global commercial and operational initiatives with a direct emphasis on accelerating Cloudera's Private AI growth.

Our Applied AI organization is a fast-moving, dedicated group of Forward Deployed Engineers (FDEs), Industry & Applied AI Specialists, and business strategy leaders committed to establishing Cloudera as the trusted standard for Private AI in the enterprise. In this high-autonomy, high-trust role, you will act as the strategic and analytical backbone behind our field engineering motions. You will prioritize the right initiatives across our strategic accounts, establish robust governance and operating rhythms, conduct deep-dive portfolio and sales pipeline analyses, and synthesize complex technical and commercial signals into actionable recommendations for Cloudera's senior leadership.

Key responsibilities:
  • Drive Global Governance & Operating Rhythms: Establish, evolve, and manage the programmatic operating rhythm for the global Applied AI organization across AMER, EMEA, and APAC. Lead the monthly business review (MBR) process-from metric gathering and CRM ingestion through deep quantitative analysis and executive synthesis for senior leadership.

  • Manage the AI Adoption Funnel: Partner with regional FDE and Applied AI Specialist leadership to track, analyze, and optimize customer progression through our four core execution stages: Discovery & Strategy, Solution & Value, Pilot & Prove, and Production & Scale.

  • Account Prioritization & Use Case Frameworks: Structure analytical frameworks grounded in real customer signal-joining technical discovery sessions, reviewing triage outcomes, and working directly with field engineering teams to filter and isolate high-ROI Private AI workloads. Conduct rigorous analyses to down-select and prioritize target accounts across our Top 100 strategic enterprise lists.

  • Define & Standardize Strategic Metrics: Collaborate with central Revenue Operations and AI GTM Sales Strategy to define, refine, and standardize key performance indicators around subscription and consumption-based Private AI adoption. Track organizational progress against critical milestones, including customer pitch meetings, on-site Use Case Workshops, Applied AI Hands-on Labs, and deployed production solutions.

  • Ecosystem & Commercial Strategy: Analyze and support go-to-market operational alignment with major AI infrastructure and ecosystem partners (including NVIDIA Blueprints and VAST). Evaluate revenue share models, joint sales plays, and co-deployment strategies to maximize platform pull-through and annual recurring revenue (ARR) expansion.

  • Cross-Functional Leadership & Solution Productization: Act as an embedded, highly trusted thought partner to technical and commercial leaders. Design and implement scalable processes for tracking team allocations and solution productization, ensuring repeatable delivery patterns are codified and communicated across Account Executives, Solution Engineers, and Professional Services globally.

  • Business Planning & Executive Storytelling: Build comprehensive segment analyses, growth models, and strategic business cases to support critical investment decisions, headcount planning, and resource allocation across regional pods.

Preferred Qualifications:
  • Strong problem-solving and structuring skills, with a proven ability to scope complex, ambiguous strategic challenges and identify root causes within technical go-to-market organizations.

  • Highly analytical and excellent at leveraging facts, CRM data, and customer insights to generate and validate strategic hypotheses regarding enterprise AI adoption and workload consumption.

  • Proven ability to communicate and build trust with stakeholders at all levels-including C-suite executives, technical engineering leaders, and regional sales VPs-by turning granular data and research into actionable insight and a well-structured executive storyline.

  • Deep familiarity with enterprise data management platforms, hybrid cloud architectures, data lakehouses (e.g., Apache Iceberg), and the broader AI/ML ecosystem capabilities.

  • Strong quantitative, financial modeling, and data manipulation skills; proficiency in GTM systems (e.g., Salesforce, Clari), business intelligence tools (e.g., Tableau, Power BI), and SQL is a strong plus.

  • Demonstrated capacity to operate with high autonomy in dynamic, fast-moving environments, building structure and operational rigor from the ground up rather than inheriting legacy processes.

Preferred Experience:
  • 6+ years of progressive work experience in sales strategy, revenue operations, business operations, or management consulting, with a demonstrated track record of driving cross-functional alignment and measurable business impact.

  • Direct experience supporting specialized technical sales, pre-sales, or post-sales delivery teams-particularly within Forward Deployed Engineering (FDE), Solution Architecture, or Applied AI Specialist organizations.

  • Deep domain experience in enterprise software, big data analytics, machine learning/AI, or hybrid cloud infrastructure companies.

  • Proven expertise working with cloud subscription, consumption-based (usage-driven), or product-led growth (PLG) business models, specifically tracking workload transition from pilot to production scale.

  • Experience supporting enterprise commercial or technical organizations through rapid 2-3x+ revenue growth periods and global expansion across AMER, EMEA, and APAC regions.

  • Note: Candidates without direct commercial ownership experience will still be strongly considered if they demonstrate long, deep tenure supporting commercial or technical sales leaders in a closely comparable enterprise GTM model.

  • The right person in this role has an opportunity to make a huge impact at Cloudera and add value to our future decisions. If this position has piqued your interest and you have what we described - we invite you apply!

  • This role is not eligible for immigration sponsorship.

The anticipated annual base salary range for this position is:

  • Washington: $144,000 - $180,000

  • New York: $144,000 - $180,000

  • California: $144,000 - $180,000

Individual compensation within the published range is determined by the candidate's skills, experience, qualifications, and primary work location. In addition to base pay, sales roles are eligible for Cloudera's commission plan, while non-sales roles are eligible for the corporate incentive plan. All employees receive a comprehensive benefits package

What you can expect from us:

  • Generous PTO Policy

  • Support work life balance with Unplugged Days

  • Flexible WFH Policy

  • Mental & Physical Wellness programs

  • Phone and Internet Reimbursement program

  • Access to Continued Career Development

  • Comprehensive Benefits and Competitive Packages

  • Paid Volunteer Time

  • Employee Resource Groups

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