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Internship Data Science Law Jobs (NOW HIRING)

Athena LLC

Interns leave with a strong understanding of industry-standard data science practices and potential references for your career.

Cypress HCM

Data Science Engineer

Austin, TX · Hybrid

$65 - $69.72/hr

Data Science Engineer Job Details * Data Science Engineer (Contract) * Location: Austin TX, 78758 ... This role is not suitable for entry-level candidates or interns. Compensation: * $65.00 to $69.72 ...

Evolver

Applied Data Science Intern

Palo Alto, CA · On-site

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In ...

Faire

Data Science Intern

San Francisco, CA

$75/hr

Data Science Internship - Fall 2026 Faire leverages machine learning and data insights to transform the wholesale industry, giving independent retailers the tools to compete with large-scale e ...

Evolver

Applied Data Science Intern

Palo Alto, CA

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In ...

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Internship Data Science Law information

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$12

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How much do internship data science law jobs pay per hour?

As of Jul 20, 2026, the average hourly pay for internship data science law in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is the difference between Internship Data Science Law vs Legal Intern?

AspectInternship Data Science LawLegal Intern
Required CredentialsBasic knowledge of data science, programming, law fundamentalsLaw students, legal studies background
Work EnvironmentLegal firms, tech companies, law departmentsLaw firms, courts, legal departments
Employer & Industry UsageLegal and tech industries integrating data analysisLegal industry primarily
Common Search & ComparisonYesYes

Internship Data Science Law and Legal Intern roles both involve legal environments, but the former emphasizes data analysis skills applied to legal issues, while the latter focuses on traditional legal research and case work. The choice depends on whether you want to develop data science expertise within legal contexts or gain legal practice experience.

What cities are hiring for Internship Data Science Law jobs? Cities with the most Internship Data Science Law job openings:
What are the most commonly searched types of Data Science Law jobs? The most popular types of Data Science Law jobs are:
What states have the most Internship Data Science Law jobs? States with the most job openings for Internship Data Science Law jobs include:
Internship Data Science Law jobs near you
Data Science Internship (Data Platforms)

Data Science Internship (Data Platforms)

MHI

Lake Mary, FL • On-site

Internship

Posted 11 days ago

Job description

Data Science Associate
Company Overview
At Mitsubishi Power, we're not just building better clean energy technologies; we're architecting a better future. Our team is boldly redefining power generation to accelerate the world's energy transition. We operate as one team, pushing toward our vision of the future. We value problem solvers, prioritize collaboration, and support each other in an inclusive culture built on accountability and authenticity by demonstrating our values: Safety, Family, Innovative, Inclusive, Accountable & Courageous. Together, we're building the future we all aspire to - making net zero a reality.
Role Overview
The Data Scientist Intern supports Mitsubishi Power's IT Data Platforms team by contributing to data quality, data cataloging, and automation efforts within enterprise data environments. This hands-on internship provides practical experience working with cloud-based data platforms, centralized data repositories, and Microsoft Power Platform tools. The role collaborates with Data Platforms leadership, Enterprise Applications, and IT stakeholders to support scalable, high-quality data solutions used across the business.
Key Responsibilities
  • Assist with data quality assessments across enterprise data sources, identifying gaps, inconsistencies, and improvement opportunities.
  • Support data catalog activities including documentation of datasets, metadata, data definitions, and lineage.
  • Validate, organize, and prepare ingested data within centralized platforms such as data lakes and structured repositories.
  • Contribute to automation efforts to surface data into Microsoft Power Apps and Power Automate workflows.
  • Perform data validation and reconciliation to ensure accuracy and completeness between source and ingested data.
  • Assist with development of basic dashboards, reports, and visualizations to support data visibility and usage.
  • Support testing and user acceptance activities to validate data processes and automation solutions.
  • Maintain tracking artifacts such as data quality logs, catalog trackers, and automation inventories.
  • Document data processes, standards, and learnings to support long-term platform sustainability.

Requirements
  • Assist with data quality assessments across enterprise data sources, identifying gaps, inconsistencies, and improvement opportunities.
  • Support data catalog activities including documentation of datasets, metadata, data definitions, and lineage.
  • Validate, organize, and prepare ingested data within centralized platforms such as data lakes and structured repositories.
  • Contribute to automation efforts to surface data into Microsoft Power Apps and Power Automate workflows.
  • Perform data validation and reconciliation to ensure accuracy and completeness between source and ingested data.
  • Assist with development of basic dashboards, reports, and visualizations to support data visibility and usage.
  • Support testing and user acceptance activities to validate data processes and automation solutions.
  • Maintain tracking artifacts such as data quality logs, catalog trackers, and automation inventories.
  • Document data processes, standards, and learnings to support long-term platform sustainability.

Learning Outcomes
  • Gain hands-on experience with enterprise data platforms, including data lakes and cloud-based environments, understanding how data supports business operations.
  • Develop core data skills in data quality, validation, cataloging, and metadata management using real-world datasets.
  • Apply analytics and automation tools such as Excel, SQL, and Microsoft Power Platform to support business processes and workflows.
  • Strengthen problem-solving and communication skills by working cross-functionally and translating data insights into clear, actionable outcomes.

Mitsubishi Power is an Equal Employment Opportunity (EEO) employer actively seeking to diversify the workforce and is committed to a policy of equal employment opportunity. Therefore, all qualified applicants regardless of race, color, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally recognized protected basis under applicable law, are strongly encouraged to apply.

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