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Google Data Science Jobs in Arizona (NOW HIRING)

... , and Data Science teams to integrate Google Chronicle's capabilities into the SOC, enhancing threat detection and incident resolution. • Optimize Google Chronicle for log management, threat ...

Junior Tableau Developer

Tucson, AZ · On-site

$64K - $83K/yr

... apple, google, Paypal, western union, Client, visa, walmart lab s etc to name a few. We are ... We need Data Science/Machine learning/Data Analyst and Java Full stack candidates Preferred SKILLS ...

Lead AI and Data Solutions Engineer II

Tempe, AZ · On-site

$98K - $129K/yr

Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, Mathematics ... Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) * 4+ years of experience ...

$18/hr

... Data Science, or related technologies. • Data management, data analytics, ETL concepts, or ... or Google Workspace and basic data visualization tools. Skills In: • Analytics and problem ...

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

Bachelor's degree in Computer Science, Data Science, or a related field. Technical Skills: * 5+ ... Familiarity with cloud-based data storage (AWS S3, Google Cloud Storage, etc.) and distributed ...

C++ Developer

Phoenix, AZ · On-site

$48.75 - $65.50/hr

... google, Paypal, Western Union, Client, visa, Walmart lab s etc to name a few. Currently, We are ... Data Scientists, and Machine Learning engineers for full-time positions with clients. Who Should ...

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

Bachelor's degree in Computer Science, Data Science, or a related field. Technical Skills: * 5+ ... Familiarity with cloud-based data storage (AWS S3, Google Cloud Storage, etc.) and distributed ...

... Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions ... Engineering, Data Science, and Data Governance - Architecting and implementing cloud-based ...

Google AI Lead Architect

Tempe, AZ · On-site

$53 - $72.50/hr

Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs ... Bachelor's degree in Computer Science, Engineering or a related technical field. * 8+ years ...

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Google Data Science information

Can data scientists make $300k?

Data scientists, including those working at Google, can earn $300,000 or more annually, especially with senior roles, extensive experience, advanced skills in machine learning and big data tools, and in high-cost-of-living areas. Compensation often includes base salary, bonuses, and stock options, which contribute to total earnings at this level.

What are the key skills and qualifications needed to thrive in the Google Data Science position, and why are they important?

To thrive as a Google Data Science professional, you need a strong foundation in statistical analysis, machine learning, and data manipulation, often supported by a degree in a quantitative field such as computer science, statistics, or mathematics. Proficiency in programming languages like Python or R, experience with large-scale data processing tools (such as SQL, TensorFlow, or BigQuery), and familiarity with cloud-based platforms are commonly required. Excellent problem-solving, communication, and collaboration skills help set candidates apart in effectively translating complex data insights to varied stakeholders. These capabilities are crucial for driving impactful, data-driven decisions within cross-functional teams at Google.

How much does Google pay a Data Scientist?

Google Data Scientists typically earn a base salary ranging from $120,000 to $180,000 annually, with total compensation often including bonuses and stock options that can increase overall earnings. Compensation varies based on experience, location, and skill level, with advanced skills in machine learning and data analysis tools being highly valued.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist, including at age 40. Success in data science depends on skills, experience, and continuous learning of tools like Python, R, and SQL, rather than age. Many professionals transition into data science later in their careers and find opportunities with relevant certifications and a strong portfolio.

What is a Google Data Science job?

A Google Data Science job involves analyzing large datasets to provide insights and drive data-informed decisions. Data scientists at Google apply statistical modeling, machine learning, and analytical techniques to solve complex problems in products like Search, Ads, YouTube, and Cloud. They work closely with engineers, product managers, and business teams to develop data-driven solutions. Strong coding skills in Python or SQL, experience with big data tools, and a solid foundation in statistics are essential for this role.

What types of projects do Google Data Science professionals typically work on?

Google Data Science professionals engage in a wide variety of impactful projects, such as optimizing algorithms for product recommendations, improving user experiences through data-driven insights, and developing predictive models to inform business strategies. They often work closely with product managers, engineers, and designers to translate complex data findings into actionable solutions. The work environment is highly collaborative and fast-paced, with opportunities to contribute to innovative initiatives across different Google products and services. This dynamic setting allows data scientists to continuously expand their skill sets and take on new challenges, fostering both personal and professional growth.

What is the average salary for a Data Scientist at Google?

The average salary for a Data Scientist at Google is approximately $120,000 to $150,000 per year, depending on experience, location, and level. Senior roles or those with specialized skills in machine learning and data analysis can earn higher compensation, often including bonuses and stock options.
What are popular job titles related to Google Data Science jobs in Arizona? For Google Data Science jobs in Arizona, the most frequently searched job titles are:
What cities in Arizona are hiring for Google Data Science jobs? Cities in Arizona with the most Google Data Science job openings:
Infographic showing various Google Data Science job openings in Arizona as of June 2026, with employment types broken down into 1% As Needed, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Forward Deployed Engineer, Frontier GenAI

Forward Deployed Engineer, Frontier GenAI

Deloitte

Tempe, AZ • On-site

Other

Posted 16 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

57th of 139 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Frontier GenAI FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with one of the following Frontier GenAI Platforms: Anthropic, Google or Open AI, including hands on experience with one of the following key platforms/products; Claude API, Claude for Enterprise, tool use, extended thinking, Claude Code, Gemini API, Vertex AI Agent Builder, Grounding, Google Workspace integration, GPT-4o, Assistants API, Responses API, OpenAI Agents SDK
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Frontier GenAI FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with one of the following Frontier GenAI Platforms: Anthropic, Google or Open AI, including hands on experience with one of the following key platforms/products; Claude API, Claude for Enterprise, tool use, extended thinking, Claude Code, Gemini API, Vertex AI Agent Builder, Grounding, Google Workspace integration, GPT-4o, Assistants API, Responses API, OpenAI Agents SDK
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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