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Entry Level Data Analyst Ai Jobs in Maple Grove, MN

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

As a Data Protection Senior Analyst, you'll support the delivery of data protection, data ... Contribute to emerging areas such as AI and agentic AI security, under guidance. . Qualifications ...

Contributes to digital transformation initiatives through the application of AI, data, automation ... Support process analysis and fit-gap assessments to assist solution design and implementation ...

Contributes to digital transformation initiatives through the application of AI, data, automation ... Support process analysis and fit-gap assessments to assist solution design and implementation ...

AI Solution Analyst

Minneapolis, MN · On-site

$60 - $80/hr

Contributes to digital transformation initiatives through the application of AI, data, automation ... Support process analysis and fit-gap assessments to assist solution design and implementation ...

ASIC Gen-AI Data Scientist

Minneapolis, MN · On-site +1

$119K - $286K/yr

Familiarity with modern AI coding tools / agentic coding harnesses, such as Claude Code, Cursor ... Experience with data analytics and visualization to deliver actionable engineering insights using ...

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Entry Level Data Analyst Ai information

See Maple Grove, MN salary details

$13

$33

$63

How much do entry level data analyst ai jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for entry level data analyst ai in Maple Grove, MN is $33.71, according to ZipRecruiter salary data. Most workers in this role earn between $21.68 and $37.64 per hour, depending on experience, location, and employer.

What is an entry level data analyst AI?

Entry level data analyst AI jobs involve collecting, cleaning, and interpreting data to help organizations make informed decisions, with a focus on supporting artificial intelligence projects. These roles may include preparing datasets for machine learning models, analyzing trends, and creating reports or visualizations. While these positions require strong analytical and problem-solving skills, they are suitable for those beginning their career in data analysis and AI, often requiring knowledge of basic programming languages, statistics, and data tools.

What are the key skills and qualifications needed to thrive as an entry level data analyst AI?

To thrive as an Entry Level Data Analyst, you need a solid understanding of statistics, data cleaning, and foundational analytics concepts, often supported by a degree in a related field such as mathematics, statistics, or computer science. Familiarity with tools like Excel, SQL, and data visualization software (e.g., Tableau or Power BI), as well as basic knowledge of programming languages like Python or R, is typically expected. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for clearly interpreting and presenting data insights. These skills and qualifications are vital for accurately analyzing data, supporting business decisions, and effectively collaborating with team members.

What are some common challenges faced by entry level data analysts working with AI projects, and how can they overcome them?

Entry-level Data Analysts in AI projects often face challenges such as understanding complex data structures, adapting to rapidly evolving tools, and interpreting results from advanced machine learning models. Collaborating closely with data scientists and engineers can help bridge knowledge gaps and foster learning. Staying proactive in seeking mentorship, participating in code reviews, and dedicating time to continuous learning are effective strategies to overcome these hurdles and quickly grow in the role.

How to become an entry level data analyst AI?

To become an entry-level data analyst AI, you should develop skills in programming languages like Python or R, learn data manipulation and analysis techniques, and gain familiarity with AI and machine learning concepts. Earning relevant certifications or completing online courses can also improve your prospects, along with experience using tools such as SQL, Excel, and data visualization software.

Is an entry level data analyst in demand with AI?

Entry level data analysts are in increasing demand as AI technologies expand, requiring skills in data manipulation, statistical analysis, and tools like Python or SQL. Organizations seek these roles to interpret data for AI model development and decision-making, making it a growing field for new professionals.

What are popular job titles related to Entry Level Data Analyst Ai jobs in Maple Grove, MN?

For Entry Level Data Analyst Ai jobs in Maple Grove, MN, the most frequently searched job titles are:

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The top searched job categories for Entry Level Data Analyst Ai jobs in Maple Grove, MN are:

What cities near Maple Grove, MN are hiring for Entry Level Data Analyst Ai jobs?

Cities near Maple Grove, MN with the most Entry Level Data Analyst Ai job openings:

Infographic showing various Entry Level Data Analyst Ai job openings in Maple Grove, MN as of June 2026, with employment types broken down into 4% As Needed, 80% Full Time, and 16% Part Time. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $70,127 per year, or $33.7 per hour.

Consultative Offerings - Analyst - Data & AI Solutions Engineering

Deloitte

Minneapolis, MN • On-site

Full-time

Re-posted 20 days ago


Key responsibilities

  • Work on designing, building, and operationalizing data-driven solutions using AI, automation, and deployment platforms.

  • Support clients by leveraging data and AI to inform decision-making, develop measurement solutions, and transform business processes.

  • Contribute to the development of scalable data pipelines, AI-powered systems, and client solutions through collaboration and technical implementation.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

48th of 154 rated financial services


Job description

Are you ready to go beyond your potential and reach something greater? At Deloitte, we believe in more than just growth-we believe in exponential possibilities. Here, your unique talents and ambitions are amplified by the power of our collaborative teams, innovative thinking, and mentorship. When you join Deloitte, you don't just build a career-you unlock unlimited opportunities, shaping your future and the world around you. Take the power of you and put it to the power of Deloitte. Reach your exponential! 

Recruiting for this role ends on 11/01/2026. 

Work You'll Do 

As a Data & AI Solutions Engineering Analyst, you won't just write code or build dashboards-you'll solve some of the most pressing business and societal challenges of today using data, intelligence, and creativity. We're looking for individuals who think critically, act boldly, and are ready to take ownership in fast-moving environments. 

You'll work at the intersection of AI engineeringdata infrastructure, and forward deployment, contributing to client solutions that go beyond analysis and into activation, building data-driven solutions with speed, scale, and substance. You won't stop at insights - you'll operationalize intelligence through platforms, automation, and integrated deployment. From designing agentic workflows that automate decision-making to building pipelines that fuel generative AI models, you'll be empowered to think like an entrepreneur and deliver like an engineer. 

Curious what this might look like in action? Our Data & AI Solutions Engineering Analysts engage in the following types of work... 

AI & Engineering - Responsible for leveraging the power of data and artificial intelligence (AI) to inform data-driven decisions at various levels, including providing insights from data using computational and AI-driven analyses and processes to support data-driven decision making as well as developing and maintaining measurement solutions and capabilities. 

Advertising, Marketing & Commerce - Responsible for supporting clients in enabling and transforming business processes through technology, but can also leverage data management, analytics, and AI to solve marketer-focused business challenges across a variety of domains by using quantitative and qualitative data analytics, that contribute to comprehensive research, statistical analysis, and data management.  

Regulatory Risk & Forensic - Responsible for architecting risk-based technology and analytics, analyzing enterprise organization risks, and delivering platform requirements for mitigation. Supports digital transformation, manages legacy systems, and uses AI/data analysis to design solutions. Provides strategic direction on Data, Modeling, and AI risks, develops governance strategies, and collaborates to align capabilities and expand into new markets. 

 

Strategy & Transactions - Responsible for leveraging scientific problem-solving, applied AI/ML, human-centered design, and data science to diagnose and solve complex, often ambiguous business challenges that have not been solved before, across client domains and industries. Applies analytical rigor and technical depth - not just implementation - to frame the problem, select the right method, and build, evaluate, and communicate solutions that drive innovation and informed decision-making for clients. Demonstrates the curiosity, adaptability, and cross-domain thinking of a scientific generalist, with a genuine passion for applying rigorous problem-solving to real-world challenges. 

 
Regardless of project type your work may include: 

  • Proficiency in scripting languages and data visualization platforms, with the ability to extract, transform, merge, and analyze data sets for actionable business insights 
  • Solid grasp of the data lifecycle, analytics concepts, and the solutions development process, paired with strong problem-solving and critical thinking skills to drive innovation and operational improvements 
  • Excellent verbal and written communication skills, along with the ability to work independently, manage multiple projects, and collaborate effectively with Deloitte teams and client stakeholders 
  • Willingness and ability to learn and implement new concepts, frameworks, and emerging technologies, demonstrating a commitment to ongoing personal and professional development 

What Makes You Stand Out 

  • Agentic AI thinking: You're not just building models-you're building AI-powered systems that observe, decide, and act with autonomy and alignment. 
  • Data engineering fluency: You understand that robust, scalable data pipelines and architectures are critical to building performant AI. 
  • Entrepreneurial energy: You bring initiative, speed, and creativity-crafting MVPs, iterating fast, and thinking like a product owner. 
  • Forward deployed presence: You thrive in real-time collaboration with client stakeholders, bringing technical ideas to life in their environment. 
  • Critical and systems thinking: You see the big picture, reason through tradeoffs, and architect holistic solutions. 
  • Deployment & Governance mindset: You don't just ship agents-you instrument them, knowing when to add human checkpoints, guardrails, and audit trails so autonomy doesn't outpace accountability. 

The Team 

Our Deloitte team plays a major role in directly embedding technology insights into our clients' organizational goals. At Deloitte, our consultants create sharply-focused solutions within an organization's operating model, accounting for its people, intellectual capital, technology, and processes. Engagement teams at Deloitte drive value for our clients but also understand the importance of developing resources and contributing to the communities in which we work. We make it our business to take issue to impact, both within and beyond a client setting.  

  

Required Qualifications 

  • Must be currently enrolled in an accredited college or university and expected to graduate by {completed by Spring/Summer 2027} or have completed a bachelor's degree or higher in Computer Science, Data Science, Statistics, Applied Math, Data Analytics, Management Information Systems, Economics, Finance, Business Analytics, Mathematics, Engineering, or a related/equivalent program 
  • Strong academic track record (minimum cumulative GPA of 3.0) 
  • Experience or coursework in data processing and analysis tools (e.g., SQL, Python, R, Power BI, Informatica), and familiarity with analytics, data visualization, or big data platforms (e.g., Tableau, Hadoop, Spark, AWS, Azure, Google Cloud) 
  • Ability to travel up to 50%, on average, based on the work you do and the clients and industries/sectors you serve 
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future 
  • Candidates must be at least 18 years of age at time of employment 
  • You must reside within a commutable distance of your assigned office with the ability to commute daily, if required 

Preferred Qualifications 

  • Cumulative GPA of 3.2 
  • Relevant professional experience, such as internships or part-time roles in analytics, data science, or related fields 
  • Hands-on experience with LLMs, vector databases, or generative AI APIs (e.g., OpenAI, Claude, Cohere). 
  • Knowledge of MLOps, CI/CD, and model deployment strategies. 
  • Internship or project experience in analytics, software engineering, or AI. 
  • Demonstrated leadership in campus orgs, startups, open-source contributions, or volunteer initiatives. 
  • Familiarity with a range of analytics, programming, and cloud tools (e.g., SQL, Python, R, Java, Tableau, Power BI, Hadoop, Spark, AWS, Azure, Google Cloud, machine learning frameworks such as TensorFlow or PyTorch) 

This is an entry-level opportunity intended for candidates interested in beginning or building a career in this field. We welcome applicants from a range of educational and professional backgrounds who meet the qualifications for the role. For roles that require a year or more of work experience, please review the experienced jobs within our careers site. 

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 is $100,000. 

Qualifications:

Are you ready to go beyond your potential and reach something greater? At Deloitte, we believe in more than just growth-we believe in exponential possibilities. Here, your unique talents and ambitions are amplified by the power of our collaborative teams, innovative thinking, and mentorship. When you join Deloitte, you don't just build a career-you unlock unlimited opportunities, shaping your future and the world around you. Take the power of you and put it to the power of Deloitte. Reach your exponential! 

Recruiting for this role ends on 11/01/2026. 

Work You'll Do 

As a Data & AI Solutions Engineering Analyst, you won't just write code or build dashboards-you'll solve some of the most pressing business and societal challenges of today using data, intelligence, and creativity. We're looking for individuals who think critically, act boldly, and are ready to take ownership in fast-moving environments. 

You'll work at the intersection of AI engineeringdata infrastructure, and forward deployment, contributing to client solutions that go beyond analysis and into activation, building data-driven solutions with speed, scale, and substance. You won't stop at insights - you'll operationalize intelligence through platforms, automation, and integrated deployment. From designing agentic workflows that automate decision-making to building pipelines that fuel generative AI models, you'll be empowered to think like an entrepreneur and deliver like an engineer. 

Curious what this might look like in action? Our Data & AI Solutions Engineering Analysts engage in the following types of work... 

AI & Engineering - Responsible for leveraging the power of data and artificial intelligence (AI) to inform data-driven decisions at various levels, including providing insights from data using computational and AI-driven analyses and processes to support data-driven decision making as well as developing and maintaining measurement solutions and capabilities. 

Advertising, Marketing & Commerce - Responsible for supporting clients in enabling and transforming business processes through technology, but can also leverage data management, analytics, and AI to solve marketer-focused business challenges across a variety of domains by using quantitative and qualitative data analytics, that contribute to comprehensive research, statistical analysis, and data management.  

Regulatory Risk & Forensic - Responsible for architecting risk-based technology and analytics, analyzing enterprise organization risks, and delivering platform requirements for mitigation. Supports digital transformation, manages legacy systems, and uses AI/data analysis to design solutions. Provides strategic direction on Data, Modeling, and AI risks, develops governance strategies, and collaborates to align capabilities and expand into new markets. 

 

Strategy & Transactions - Responsible for leveraging scientific problem-solving, applied AI/ML, human-centered design, and data science to diagnose and solve complex, often ambiguous business challenges that have not been solved before, across client domains and industries. Applies analytical rigor and technical depth - not just implementation - to frame the problem, select the right method, and build, evaluate, and communicate solutions that drive innovation and informed decision-making for clients. Demonstrates the curiosity, adaptability, and cross-domain thinking of a scientific generalist, with a genuine passion for applying rigorous problem-solving to real-world challenges. 

 
Regardless of project type your work may include: 

  • Proficiency in scripting languages and data visualization platforms, with the ability to extract, transform, merge, and analyze data sets for actionable business insights 
  • Solid grasp of the data lifecycle, analytics concepts, and the solutions development process, paired with strong problem-solving and critical thinking skills to drive innovation and operational improvements 
  • Excellent verbal and written communication skills, along with the ability to work independently, manage multiple projects, and collaborate effectively with Deloitte teams and client stakeholders 
  • Willingness and ability to learn and implement new concepts, frameworks, and emerging technologies, demonstrating a commitment to ongoing personal and professional development 

What Makes You Stand Out 

  • Agentic AI thinking: You're not just building models-you're building AI-powered systems that observe, decide, and act with autonomy and alignment. 
  • Data engineering fluency: You understand that robust, scalable data pipelines and architectures are critical to building performant AI. 
  • Entrepreneuri...

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