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Generative Ai Analyst Jobs in Delaware (NOW HIRING)

Mwe

Senior Manager, AI & Analytics

Wilmington, DE · On-site

Working knowledge of generative AI, intelligent automation, prompt engineering, and responsible AI ... Analytics, Computer Science, or related field required * Master's degree, MBA, CPA, CMA, or ...

Bancorp Bank

... data science, advanced analytics, or related enterprise technology functions. * 5+ years of ... Strong understanding of AI/ML, generative AI, NLP, intelligent automation, workflow orchestration ...

Morson Talent

AI Adoption Specialist

Wilmington, DE · On-site +1

$35 - $45/hr

Create, test, and refine prompts for generative AI applications. Participate in prompt tuning and ... At least 1 year of experience in data science, analytics, automation, or AIrelated work. Desired ...

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Generative Ai Analyst information

See Delaware salary details

$49K

$88.6K

$123.6K

How much do generative ai analyst jobs pay per year?

As of Sep 12, 2026, the average yearly pay for generative ai analyst in Delaware is $88,645.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,100.00 and $99,600.00 per year, depending on experience, location, and employer.

What is a generative AI analyst?

A Generative AI Analyst is a professional who specializes in analyzing, designing, and optimizing systems that use generative artificial intelligence models, such as large language models or image generators. Their work involves understanding how these AI models are developed, deployed, and utilized across various applications. They assess data quality, monitor model outputs, evaluate performance, and help improve the effectiveness and ethical use of generative AI technologies. Generative AI Analysts may also provide insights to organizations on best practices, risk management, and innovation opportunities related to AI. Their expertise bridges the gap between data science, AI development, and business strategy.

What are the key skills and qualifications needed to thrive as a generative AI analyst?

To thrive as a Generative AI Analyst, you need a solid background in data science, machine learning, and statistics, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, and experience with large language models or generative adversarial networks (GANs) is typically required. Strong analytical thinking, creativity, and effective communication skills help you interpret complex data and present insights to stakeholders. These skills and qualities are crucial for developing innovative AI solutions, solving business challenges, and driving impactful results.

How does a generative AI analyst typically collaborate with data scientists and engineering teams?

A Generative AI Analyst frequently works alongside data scientists and engineering teams to interpret model outputs, assess data quality, and help translate business objectives into technical requirements. Collaboration usually involves regular meetings to review model performance, troubleshoot issues, and refine algorithms based on real-world feedback. Effective communication and a shared understanding of both AI concepts and business goals are essential, as the analyst often serves as a bridge between technical teams and stakeholders. This collaborative environment fosters continuous learning and innovation, making teamwork a core aspect of the role.

What is the difference between Generative Ai Analyst vs Data Scientist?

AspectGenerative Ai AnalystData Scientist
Required CredentialsBachelor's in CS, AI, or related fields; certifications in AI/MLBachelor's/Master's in CS, Statistics, or related fields; advanced certifications
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, consulting
Employer & Industry UsageFocus on developing and refining generative AI modelsAnalyze data, build predictive models, derive insights
Common Search & Comparison IntentUnderstanding roles in AI developmentData analysis and modeling skills

While both roles require strong technical skills and knowledge of AI and data analysis, a Generative Ai Analyst specializes in creating and optimizing generative AI models, whereas a Data Scientist focuses on analyzing data to inform business decisions. The roles often overlap but differ in their primary focus and application within organizations.

How much do generative AI analysts make?

Generative AI analysts typically earn between $70,000 and $130,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and deep learning can command higher salaries, often exceeding $150,000.

Is Generative AI a promising career?

Generative AI is a rapidly growing field with increasing demand for specialists such as Generative AI Analysts, who develop and refine AI models like GPT and DALL·E. Careers in this area often require skills in machine learning, programming, and data analysis, and offer opportunities across technology, healthcare, entertainment, and other industries. The field is expected to continue expanding as AI applications become more integrated into various sectors.

What are popular job titles related to Generative Ai Analyst jobs in Delaware?

For Generative Ai Analyst jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Generative Ai Analyst jobs in Delaware look for?

The top searched job categories for Generative Ai Analyst jobs in Delaware are:

What cities in Delaware are hiring for Generative Ai Analyst jobs?

Cities in Delaware with the most Generative Ai Analyst job openings:

Generative Ai Analyst jobs near you
Infographic showing various Generative Ai Analyst job openings in Delaware as of June 2026, with employment types broken down into 60% Full Time, 37% Part Time, and 3% Contract. Highlights an 69% Physical, 3% Hybrid, and 28% Remote job distribution, with an average salary of $88,645 per year, or $42.6 per hour.

Vice President, Digital Marketing Analytics

Wilmington, DE • On-site

JPMorgan Chase & Co.
Finance and Insurance • 10K+ employees
Learn more about JPMorgan Chase & Co.external

Other

Posted 23 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

Job description

You will help shape digital marketing strategy through rigorous analysis, experimentation, and clear storytelling that drives business outcomes. You will work with partners across Marketing, Finance, Product, and Technology to turn complex questions into measurable actions. You will grow and lead a high-performing analytics team, building scalable, reliable ways of working that improve how marketing decisions are made.

As a Vice President, Digital Marketing Analytics at JPMorganChase within the Digital Marketing Analytics team, you will lead quantitative research and experimentation to optimize marketing performance and customer experiences. You will translate customer behavior and campaign performance into insights that leaders can act on, and you will build team capability through coaching, hiring, and a culture of scientific rigor and responsible use of advanced analytics. You will take a pragmatic approach to generative AI and large language models (LLMs) as complementary tools, while relying on classical statistical and causal methods for core measurement and optimization workstreams.

Job responsibilities
  • Deliver effective quantitative problem solving and analytical research to support key digital marketing initiatives
  • Apply deep business understanding and advanced analytical techniques to drive research, experimentation, and measurable outcomes
  • Lead, mentor, hire, and develop a high-performing analytics team; promote scientific rigor, ethical AI, and continuous learning
  • Maintain a pragmatic approach to generative AI and large language models (LLMs) as complementary tools, prioritizing classical statistical methods for core measurement and optimization work
  • Partner with cross-functional teams (for example, Marketing and Finance) to drive insights into action and deliver business impact
  • Design and implement scalable, reliable analytics processes to optimize business outcomes
  • Conduct extensive analysis of marketing performance, measurement configuration and settings, and customer behavior to improve channel strategies and optimization using advanced quantitative methods
  • Own and support strategic measurement initiatives, including effectiveness evaluation and profit and loss analysis; quantify statistical and practical significance
  • Solve unstructured business problems and develop deep-dive analyses of customer behavior using multiple analytics and statistical techniques
  • Conduct hypothesis testing and advanced experimental design (A/B and multivariate tests) to measure the impact and effectiveness of marketing strategies
Required qualifications, capabilities and skills
  • Graduate or post-graduate degree in a quantitative discipline (for example, Computer Science, Statistics, Mathematics, Finance, Economics, Data Analytics, or Machine Learning)
  • 5+ years of hands-on analytics experience in banking strategic analytics
  • Hands-on proficiency with Python and SQL; experience with visualization tools (for example, Tableau) and analytics tools (for example, Alteryx)
  • Experience with Adobe Analytics (implementation, reporting, and insight generation)
  • Strong statistical or econometric foundation with hands-on experimentation and measurement experience, including A/B testing, causal inference, and experimentation frameworks
  • Strong advanced analytics skills using SAS, Python, or R
  • Excellent communication skills with the ability to translate complex models into clear explanations and reason codes, influencing cross-functional stakeholders and senior leadership
  • Exposure to enterprise AI enablement, LLM-assisted workflows, or analytics transformation programs
  • Ability to evaluate opportunities to apply AI, generative AI, and intelligent automation to improve investigative analysis, documentation, operating procedures, knowledge retrieval, issue summarization, and workflow efficiency
  • Familiarity with supervised learning, anomaly detection, semi-supervised learning, clustering, feature stores, calibration and threshold optimization, and imbalanced learning
Preferred qualifications, capabilities and skills
  • Proficiency in big data extract, transform, and load processes across structured and unstructured data sources
  • Professional experience with AWS, Spark or EMR, and Snowflake
  • Experience with Confluence and generative AI tools (for example, ChatGPT), subject to firm-approved usage
  • People leadership experience, including recruiting, coaching, performance management, and fostering an inclusive, high-accountability culture
  • Strong understanding of IT processes and databases, with the ability to work directly with data owners and custodians
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