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Ai Data Analytics Jobs (NOW HIRING)

AI Data Engineer

San Francisco, CA ยท On-site

$134K - $162K/yr

Job Title: AI Data Engineer - AWS Data Analytics & Generative AI Location - Remote Experience - 8+ Years (Data Engineering) | 2+ Years (AI/ML/Generative AI) Job Summary * We are seeking an ...

... data analytics and machine learning. You will collaborate with departments across the Town to ... AI & Machine Learning โ€ข Assist in building and monitoring AI models using SAS Viya and other ...

AI Data Architect

Cleveland, OH ยท On-site

$61.75 - $79.50/hr

AI Data Architect Location: Cleveland, OH (ONSITE) FULLTIME ONLY Must Have Technical/Functional Skills: * 10+ years in data / analytics architecture, with strong manufacturing or industrial ...

Own the product vision and strategic roadmap for our external, customer-facing AI/ML models, data products, and analytics features. * Engage directly with strategic customers and design partners to ...

AI Data Engineer

Detroit, MI

$113K - $136K/yr

Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics. * Optimize cloud infrastructure: Utilize AWS cloud computing platforms to ...

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Ai Data Analytics information

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How much do ai data analytics jobs pay per hour?

As of Jun 28, 2026, the average hourly pay for ai data analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

How much does an AI data analyst make?

The average salary for an AI data analyst ranges from $70,000 to $120,000 annually, depending on experience, location, and industry. Professionals with strong skills in data modeling, machine learning, and tools like Python or R tend to earn higher salaries.

Which 3 jobs will survive AI?

AI Data Analysts, data scientists, and machine learning engineers are likely to continue thriving as their roles involve complex analysis, model development, and interpretation that require human expertise. These jobs demand skills in statistics, programming, and critical thinking, making them less susceptible to automation. Continuous learning and proficiency with AI tools are essential for long-term job security in these fields.

What is the difference between Ai Data Analytics vs Data Scientist?

AspectAi Data AnalyticsData Scientist
Required CredentialsBachelor's in Data Science, Computer Science, or related fields; certifications in AI and data analyticsBachelor's or higher in Data Science, Statistics, Computer Science; advanced degrees preferred
Work EnvironmentTech companies, finance, healthcare; focus on AI-driven data analysisResearch labs, tech firms, finance; focus on data modeling and insights
Employer & Industry UsageUsed in industries leveraging AI for predictive analytics and automationUsed across industries for data modeling, predictive analytics, and research

Ai Data Analytics professionals focus on applying AI techniques to analyze data and develop automated solutions, while Data Scientists build models and interpret data to generate insights. Both roles require strong analytical skills and familiarity with data tools, but Ai Data Analytics emphasizes AI implementation, whereas Data Scientists focus on statistical modeling and research.

How does an AI Data Analytics professional typically collaborate with cross-functional teams within an organization?

AI Data Analytics professionals frequently work alongside departments such as marketing, operations, IT, and product development to interpret complex datasets and provide actionable insights. Collaboration often involves translating business needs into data-driven solutions, communicating findings in accessible terms, and ensuring that analytics projects align with organizational goals. Effective teamwork and clear communication are crucial, as analytics professionals must bridge the gap between technical data analysis and practical business application.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as AI executives, senior data scientists, or machine learning directors, often requiring advanced skills, extensive experience, and sometimes equity or performance-based bonuses. These positions are usually found in large tech companies or organizations investing heavily in AI development and may involve leadership, strategic planning, and specialized technical expertise.

What are the key skills and qualifications needed to thrive as an AI Data Analyst, and why are they important?

To thrive as an AI Data Analyst, you need a strong background in statistics, data analysis, and machine learning, typically supported by a degree in computer science, mathematics, or a related field. Proficiency with tools such as Python, R, SQL, and data visualization platforms like Tableau, along with knowledge of AI frameworks such as TensorFlow or PyTorch, is essential. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex data and present actionable insights to stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the impact of AI initiatives within organizations.

What is AI Data Analytics?

AI Data Analytics refers to the use of artificial intelligence technologies to analyze and interpret large volumes of data. By leveraging machine learning algorithms, natural language processing, and other AI methods, professionals in this field can uncover patterns, make predictions, and drive data-driven decision-making. AI Data Analytics is widely used across industries to optimize operations, improve customer experiences, and gain competitive insights. The role typically involves working with big data platforms, developing models, and communicating findings to stakeholders.

What does an AI data analyst do?

An AI data analyst collects, processes, and analyzes large datasets to extract insights that inform business decisions. They use tools like Python, R, and machine learning algorithms to identify patterns and trends, often working with AI models to improve data-driven solutions. Strong analytical skills and knowledge of data visualization are essential in this role.
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What states have the most Ai Data Analytics jobs? States with the most job openings for Ai Data Analytics jobs include:
Staff AI Data Analytics Engineer

Staff AI Data Analytics Engineer

Symbotic

Wilmington, MA โ€ข Hybrid

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 19 days ago


Job description

Who we are

With its A.I.-powered robotic technology platform, Symbotic is changing the way consumer goods move through the supply chain. Intelligent software orchestrates advanced robots in a high-density, end-to-end system - reinventing warehouse automation for increased efficiency, speed and flexibility.

What we need

We are looking for an AI Analytics Engineer to join Symbotic. Your job will be to design and build an intelligent analytics ecosystem that aggregates operations data across multiple systems and leverages agentic AI to generate insights, dashboards, and proactive recommendations. This individual will play a critical role in enabling scalable, real-time visibility into business performance as we grow globally, with a focus on hands-on development of robust, production-level data systems.

What you'll do

Data Integration & Modeling

  • Aggregate and unify data across disparate systems.

  • Design scalable data models and pipelines to enable reliable and real-time analytics.

AI-Driven Analytics & Reporting

  • Leverage agentic AI tools to dynamically generate reports and dashboards.

  • Build solutions that provide both real-time visibility and historical trend analysis across key business initiatives.

  • Implement AI-driven workflows to automate data analysis, reporting, insight generation, and risk mitigation strategies.

Dashboarding & Visualization

  • Develop intuitive, executive-ready dashboards that highlight key performance indicators and insights.

  • Collaborate with cross-functional analytics and business partners to align on priorities and ensure insights translate into measurable outcomes.

  • Ensure reporting is actionable and aligned to business priorities.

Risk Identification & Actionable Recommendations

  • Analyze data to identify risks, inefficiencies, and performance gaps

  • Provide clear, data-driven recommendations to mitigate risks and improve outcomes.

Data Governance

  • Establish and enforce enterprise-wide data governance and standards, including clear ownership of core metrics across systems, metric definitions, calculation methodologies, source-of-truth alignment across systems.

  • Lead data governance and data quality efforts, includingidentifyingand remediating inconsistencies across data sources and pipelines, and ensuring accuracy, consistency, and trust in analytics outputs.

What you'll need

  • Bachelor's degree or higher in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.

  • Minimum of 8 years of experience in Data Engineering, Analytics Engineering, or Data Science with a strong foundation in statistical analysis and data modeling.

  • Experience building agentic AI frameworks for analytics automation.

  • Strong proficiency in SQL and Python (data manipulation, analysis, automation).

  • Expertise in data visualization tools (e.g., Tableau, Power BI, Looker).

  • Experience working with large, multi-source datasets and building scalable data models.

  • Demonstrated hands-on coding capability, with experience designing, building, and maintaining production-grade data pipelines and analytics systems.

  • Experience defining and implementing data governance frameworks, including metric standardization, data ownership models, and source-of-truth alignment.

  • Strong business acumen with the ability to translate data into actionable insights.

  • Comfortable operating in a fast-paced, high-growth environment where speed, ownership, and adaptability are critical.

Our environment

  • Up to10%of travel may berequired. Employees must have a valid driver's license and the ability to drive and/or fly to client and other customer locations.

  • The employeeis responsible forowning a credit card and managing expenses personally to be reimbursed on a bi-weekly basis.

#LI-Hybrid

#LI-DW

About Symbotic

Symbotic is an automation technology leader reimagining the supply chain with its end-to-end, AI-powered robotic and software platform. Symbotic reinvents the warehouse as a strategic asset for the world's largest retail, wholesale, and food & beverage companies. Applying next-gen technology, high-density storage and machine learning to solve today's complex distribution challenges, Symbotic enables companies to move goods with unmatched speed, agility, accuracy and efficiency. As the backbone of commerce the Symbotic platform transforms the flow of goods and the economics of supply chain for its customers. For more information, visitwww.symbotic.com.

We are a community of innovators, collaborators and pioneers who embrace our differences, because we know unique perspectives make us stronger and smarter. Every perspective matters. We depend on the collective voices of our employees, customers and community to help guide us as we build a better place to work - for you and the world. That's why we're proud to be an equal opportunity employer.

We do not discriminate based on race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.

The base range for this position in the posted location is $149,000.00 - $204,600.00 however, base pay offered may vary depending on job-related knowledge, skills, and experience. The compensation package includes medical, dental, vision, disability, 401K, PTO and/or other benefits.