Entry Level AI Data Analyst Jobs
New grad ai data analyst jobs welcome recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship project can carry more weight than a lengthy resume. Most openings are across Technology & Software, Energy, and Education, with a mix of on-site, remote, and hybrid settings, and employers like C Spire, Qualcomm, and Mindlance hiring at this level now.
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INTRODUCTION
We are seeking a highly skilled AI Engineer to design and build Generative and Agentic AI systems that transform how our company operates and serves customers. This role focuses on developing AI applications powered by large language models (LLMs), retrieval-augmented generation (RAG), Model Context Protocol (MCP) servers, and Agentic AI across the enterprise for internal and customer facing use cases.
The ideal candidate has strong experience with a modern AI/ML stack, including a profound Python experience, including AI relevant packages and tools, LLM architectures and frameworks, RAG, MCP, prompt engineering, use of AI tools, building teams of AI agents, and production-grade AI systems design and development.
You will work closely with technology, data, and business teams to build scalable AI solutions that drive operational efficiency and innovation across the enterprise.
KEY RESPONSIBILITIES:
- Design, build, and deploy scalable LLM-powered applications, solutions, and digital products for customer support, business use cases, and internal productivity.
- Develop AI agents, Agentic Platforms, and Agentic AI systems capable of reasoning, planning, and executing multi-step workflows.
- Implement Retrieval-Augmented Generation (RAG) architectures and pipelines to leverage proprietary data, and internal knowledge bases.
- Build MCP servers, multi-connectivity enabled and multi-modal Agentic platforms, and AI assistants to support internal teams and customer facing.
- Integrate AI/ML solutions with enterprise systems, APIs, and data platforms.
- Design prompt strategies, evaluation frameworks, and guardrails to ensure accuracy, security, and regulatory compliance.
- Optimize LLM performance through fine-tuning, prompt engineering, and model orchestration.
- Develop MLOps and LLMOps pipelines for monitoring, evaluation, and continuous improvement of AI systems.
- Help in forming buy or build decisions and work with external vendors, consultants and internal teams to deliver scalable top-quality AI solutions timely.
- Stay up to date with emerging advancements in AI/ML, Generative AI, Agentic frameworks, and model architectures.
BASIC QUALIFICATIONS:
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or related field.
- 2+ years of software engineering experience, including work with machine learning (ML) or AI systems.
- Hands-on experience building LLM-powered applications in production environments.
- Strong programming skills in Python, and familiarity with AI/ML relevant packages such as NumPy, Pandas, SciPy and Scikit-learn.
- Experience with LLM ecosystems such as:
- OpenAI / Anthropic / Google, Open-source LLMs
- Hugging Face
- LangChain, LlamaIndex, or similar orchestration frameworks
- Experience building RAG pipelines and working with vector databases.
- Understanding of prompt engineering, embeddings, and model evaluation.
- Experience building APIs, MCPs, and scalable backend services.
- Experience with Claude Code, Codex, Cursor, GitHub Copilot, or similar.
- Ability to collaborate with cross-functional teams.
- Passion for technology and AI.
PREFERRED QUALIFICATIONS:
- Experience building AI agents, agentic platforms, or autonomous workflows.
- Familiarity with agent frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel, Frontier, etc.).
- Experience with fine-tuning LLMs or parameter-efficient training methods (LoRA, PEFT).
- Experience with cloud-based AI infrastructure (AWS, Azure, or GCP).
- Familiarity with Java, JS, and Java applications and environments.
- Experience with MLOps / LLMOps tools and evaluation pipelines.
- Experience implementing AI governance, observability, and guardrails.
SALARY RANGE:
The pay range for this position is $110,000 to $160,000 annually. Actual compensation will vary based on multiple factors, including employee knowledge and experience, role scope, business needs, geographical location, and internal equity.
PERKS AND BENEFITS:
- 4 weeks accrued paid time off + 9 paid national holidays per year
- Free onsite gym at our Boston Location
- Tuition Reimbursement
- Low cost and excellent coverage health insurance options that start on Day 1 (medical, dental, vision)
- Robust health and wellness program and fitness reimbursements
- Auto and home insurance discounts
- Matching gift opportunities
- Annual 401(k) Employer Contribution (up to 7.5% of your base salary)
- Various Paid Family leave options including Paid Parental Leave
- Resources to promote Professional Development (LinkedIn Learning and licensure assistance)
- Convenient location directly across from South Station and Pre-Tax Commuter Benefits
About the Company
The Plymouth Rock Company and its affiliated group of companies write and manage over $2.3 billion in personal and commercial auto and homeowner's insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”
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Entry Level AI Data Analyst Jobs: Frequently Asked Questions
How do I get an entry level ai data analyst job?
Entry level ai data analyst employers look for candidates who can demonstrate hands-on work with real data, even from academic projects or personal builds. A portfolio showing Python or SQL skills, familiarity with machine learning libraries like scikit-learn or TensorFlow, and at least one end-to-end analysis project gives you a concrete edge over applicants who list tools without showing results. Internship experience, bootcamp certifications, and capstone projects all count.
Which companies hire entry level ai data analysts?
Companies hiring entry level ai data analysts right now include C Spire, Qualcomm, and Mindlance, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes from a broad range of employers, including technology firms, healthcare organizations, financial services companies, and startups that are actively building out their data and AI teams.
Are there remote entry level ai data analyst jobs?
Yes, though availability varies by employer and role type. About 14% of entry level ai data analyst openings are remote or hybrid as of November 2026, making this a field with real flexibility for candidates who prefer not to relocate. Fully remote junior roles tend to be more common at tech companies and AI-focused startups than at larger legacy organizations.
Are these new grad ai data analyst jobs?
Yes, the listings on this page include new grad, recent graduate, and junior ai data analyst roles. A posting is typically new-grad friendly when it welcomes zero to two years of experience, accepts internship or academic project work in place of professional history, or explicitly invites portfolio submissions. If the job description does not require prior employment, it is a strong candidate for a new grad application.
Which industries hire the most entry level ai data analysts?
Entry Level ai data analyst roles concentrate in Technology & Software, Energy, and Education, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at the junior level because they are actively investing in AI-powered tools, predictive modeling, and data infrastructure, creating a steady need for analysts who can support those initiatives from the ground up.