Mid Level Data Science Intern Jobs
Mid level data science intern jobs call for professionals ready to own analytical pipelines end to end, drive model decisions with limited oversight, and guide junior teammates through complex problems. Openings are distributed across on-site, hybrid, and remote settings in Technology & Software, Biotechnology & Pharmaceuticals, and Retail, with Amazon, Jazz Pharmaceuticals, and Walmart hiring at this level now.
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Showing 5 of 345+ Mid Level Data Science Intern jobs
Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.
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.
Recruiting for this role ends on 7/31/2026.
Work you'll do
As an AI and Data Science Engineer III on the AI & Data team, you will be responsible for driving technology-focused client delivery across complex engagements.
Working within an engagement team, your responsibilities include, among others:
- Managing day-to-day interactions with executive clients, stakeholders, and sponsors
- Managing and delivering components of client engagements focused on identifying, designing, and implementing both technology and creative business solutions for large companies
- Managing small teams to identify business requirements, functional design, process design (including scenario design, flow mapping), prototyping, testing, training, defining support procedures. Your background in technology will provide the foundation to manage these streams but also understand the technology
- Creation and development of project scope and schedule. Plan and assign resources to associated tasks and deliverables
- Monitoring progress of the project, identify, and quantify variances, perform required corrective actions
- Managing changes to project scope, project schedule, and project costs to keep the project plan accurate, updated, as defined in the change management plan
- Identifying high-level risks, assumptions, and constraints. Implement approved actions and workarounds to minimize the impact of risks on the project
- Developing and maintaining communication with key project stakeholders and decision makers
The team
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
Qualifications
Required:
- 4+ years of experience delivering AI/ML solutions, with at least 1 year focused on Generative AI, Agentic AI or multi-agent systems
- 2+ years of hands-on experience building AI/ML solutions using Python
- 1+ years of direct experience developing agentic AI systems, including agent orchestration, tool integration, and autonomous decision-making workflows (ie: LangChain; Semantic Kernel, AutoGen, Strands; CrewAI. LangGraph) to include:
Azure: AI Foundry (design, deployment, orchestration of AI/agentic applications); OpenAI Service (LLM integration for reasoning, planning, and tool use); Cognitive Search & Vector DBs (retrieval, memory, context for agents); Cognitive Services (vision, speech, and language APIs for agent capabilities); Entra ID & Key Vault (identity, security, compliance for AI workloads);
and/or
AWS: Amazon Bedrock (foundation models, model evaluation, and agent orchestration); Knowledge bases (retrieval, metadata filtering, re-ranking), Guardrails, Prompt Flows, and RAG pipelines for enterprise-grade agentic solutions; Lambda, ECR and EC2 based deployment; Amazon Q Business & Q Developer (enterprise AI assistant and code generation capabilities); Cognito (identity, security, compliance for AI workloads); IAM, Secrets Manager, and KMS;
and/or
GCP: Vertex AI (e.g., Model Garden, Agent Builder, custom training); Gemini API and Google AI Studio; BigQuery (for data processing and analytics); Cloud Run, Cloud Functions, and GKE (for agent deployment)
- 1+ years experience leading project workstreams/engagements, translating business problems into AI solutions, and delivering measurable outcomes
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI, or related field
- Ability to travel up to 50% on average, based on the work you do and the clients and industries/sectors you serve
- Limited immigration sponsorship may be available
Preferred:
- Prior consulting experience in client-facing delivery roles
- Experience in creating critical collaterals for client workshops and customer interactive sessions
- Presentation skills with a high degree of comfort with both large and small audiences
- Experience building multi-agent systems (task delegation, coordination, and autonomous decision-making)
- Certifications: Azure AI Engineer Associate, Azure Solutions Architect Expert; AWS Certified Machine Learning - Specialty, AWS Certified Solutions Architect - Professional; Professional Machine Learning Engineer, Professional Cloud Architect
- Experience with LLM prompt engineering, fine-tuning, and RAG (Retrieval Augmented Generation) architecture
- Experience with MLOps / AIOps (monitoring, governance, lifecycle), CI/CD pipelines, and cloud-native application development
- Experience with API design, microservices architecture, and event-driven systems
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 $122,000 to $240,500.
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.
Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.
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.
Recruiting for this role ends on 7/31/2026.
Work you'll do
As an AI and Data Science Engineer III on the AI & Data team, you will be responsible for driving technology-focused client delivery across complex engagements.
Working within an engagement team, your responsibilities include, among others:
- Managing day-to-day interactions with executive clients, stakeholders, and sponsors
- Managing and delivering components of client engagements focused on identifying, designing, and implementing both technology and creative business solutions for large companies
- Managing small teams to identify business requirements, functional design, process design (including scenario design, flow mapping), prototyping, testing, training, defining support procedures. Your background in technology will provide the foundation to manage these streams but also understand the technology
- Creation and development of project scope and schedule. Plan and assign resources to associated tasks and deliverables
- Monitoring progress of the project, identify, and quantify variances, perform required corrective actions
- Managing changes to project scope, project schedule, and project costs to keep the project plan accurate, updated, as defined in the change management plan
- Identifying high-level risks, assumptions, and constraints. Implement approved actions and workarounds to minimize the impact of risks on the project
- Developing and maintaining communication with key project stakeholders and decision makers
The team
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
Qualifications
Required:
- 4+ years of experience delivering AI/ML solutions, with at least 1 year focused on Generative AI, Agentic AI or multi-agent systems
- 2+ years of hands-on experience building AI/ML solutions using Python
- 1+ years of direct experience developing agentic AI systems, including agent orchestration, tool integration, and autonomous decision-making workflows (ie: LangChain; Semantic Kernel, AutoGen, Strands; CrewAI. LangGraph) to include:
Azure: AI Foundry (design, deployment, orchestration of AI/agentic applications); OpenAI Service (LLM integration for reasoning, planning, and tool use); Cognitive Search & Vector DBs (retrieval, memory, context for agents); Cognitive Services (vision, speech, and language APIs for agent capabilities); Entra ID & Key Vault (identity, security, compliance for AI workloads);
and/or
AWS: Amazon Bedrock (foundation models, model evaluation, and agent orchestration); Knowledge bases (retrieval, metadata filtering, re-ranking), Guardrails, Prompt Flows, and RAG pipelines for enterprise-grade agentic solutions; Lambda, ECR and EC2 based deployment; Amazon Q Business & Q Developer (enterprise AI assistant and code generation capabilities); Cognito (identity, security, compliance for AI workloads); IAM, Secrets Manager, and KMS;
and/or
GCP: Vertex AI (e.g., Model Garden, Agent Builder, custom training); Gemini API and Google AI Studio; BigQuery (for data processing and analytics); Cloud Run, Cloud Functions, and GKE (for agent deployment)
- 1+ years experience leading project workstreams/engagements, translating business problems into AI solutions, and delivering measurable outcomes
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI, or related field
- Ability to travel up to 50% on average, based on the work you do and the clients and industries/sectors you serve
- Limited immigration sponsorship may be available
Preferred:
- Prior consulting experience in client-facing delivery roles
- Experience in creating critical collaterals for client workshops and customer interactive sessions
- Presentation skills with a high degree of comfort with both large and small audiences
- Experience building multi-agent systems (task delegation, coordination, and autonomous decision-making)
- Certifications: Azure AI Engineer Associate, Azure Solutions Architect Expert; AWS Certified Machine Learning - Specialty, AWS Certified Solutions Architect - Professional; Professional Machine Learning Engineer, Professional Cloud Architect
- Experience with LLM prompt engineering, fine-tuning, and RAG (Retrieval Augmented Generation) architecture
- Experience with MLOps / AIOps (monitoring, governance, lifecycle), CI/CD pipelines, and cloud-native application development
- Experience with API design, microservices architecture, and event-driven systems
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 $122,000 to $240,500.
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.
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Find JobsMid Level Data Science Intern Job Market
Who's Hiring
- Amazon35
- Jazz Pharmaceuticals17
- Walmart11
- Analytic Partners10
- Karyopharm Therapeutics9
Top Industries Hiring
- Technology & Software69
- Biotechnology & Pharmaceuticals69
- Retail50
- Education46
- E-Commerce & Online Marketplaces37
Mid Level Data Science Intern Jobs: Frequently Asked Questions
How do I get a mid level data science intern job?
Position your application around ownership and impact, not just task completion. Highlight projects where you drove decisions independently, improved a model's performance measurably, or delivered analysis that shaped a product or business outcome. Tailor your resume to show depth in a core tool set, such as Python, SQL, or machine learning frameworks, and demonstrate you can work with minimal supervision on end-to-end data workflows.
Which companies hire mid level data science interns?
Companies hiring mid level data science interns right now include Amazon, Jazz Pharmaceuticals, and Walmart, based on current listings on Migrate Mate as of July 2026. Hiring at this level tends to come from organizations scaling their data teams, including technology firms, healthcare companies, and financial services employers that need practitioners who can take on substantive projects without heavy onboarding.
Are there remote mid level data science intern jobs?
Yes, and a significant share of openings support flexible arrangements. About 40% of mid level data science intern openings are remote or hybrid as of July 2026, reflecting broad employer comfort with distributed data work. Roles requiring access to proprietary data infrastructure or on-site collaboration with product teams are more likely to be fully on-site.
How do I move up to a mid level data science intern role?
The path from entry level to mid level in data science is built through accumulated ownership. Early in your career, focus on deepening your technical foundation in areas like statistical modeling, data pipelines, or machine learning. Over time, seek out projects where you are accountable for outcomes, not just execution. Demonstrating that you can scope work, make judgment calls on methodology, and communicate findings to non-technical stakeholders signals readiness for mid level responsibility.
Which industries hire the most mid level data science interns?
Mid Level data science intern roles concentrate in Technology & Software, Biotechnology & Pharmaceuticals, and Retail, based on current listings on Migrate Mate as of July 2026. These sectors rely on data-driven decision making at scale, creating consistent demand for practitioners who can move beyond exploratory analysis and deliver production-ready models or reporting pipelines with real business impact.