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Legal Data Science Jobs (NOW HIRING)

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team The Applied Science team operates at the core of Relativity's AI development.

Support Center - Irving The Manager - Data Science role is critical in helping to determine which ... S. must satisfy federal, state, and local legal requirements of the job. At The Michaels Companies ...

Support Center - Irving The Manager - Data Science role is critical in helping to determine which ... S. must satisfy federal, state, and local legal requirements of the job. At The Michaels Companies ...

Manager, Data Science - Agentic AI

Raleigh, NC ยท On-site

$115K - $192K/yr

LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 ... The company employs over 2,000 technologists, data scientists, and experts to develop, test, and ...

Manager, Data Science - Agentic AI

Raleigh, NC ยท On-site

$115K - $192K/yr

LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 ... The company employs over 2,000 technologists, data scientists, and experts to develop, test, and ...

... Legal, Life), Defined Contribution Retirement Plan. Qualifications * Master's Degree in Data ... Master's Degree in Data Science, Computer Science, Statistics, or equivalent * 5+ years of ...

You are expected to work cross-functionally, including: engineering, product managers, lifecycle marketing, data science, design, operations, finance, risk, legal, compliance, and executive teams to ...

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Showing results 1-20

Legal Data Science information

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$27.5K

$53.3K

$85K

How much do legal data science jobs pay per year?

As of Jun 9, 2026, the average yearly pay for legal data science in the United States is $53,278.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $60,000.00 per year, depending on experience, location, and employer.

What is legal data science?

Legal data science is the application of data analysis, statistical methods, and machine learning to legal data and processes. It involves extracting, processing, and interpreting large volumes of legal documents, such as court decisions, contracts, or case filings, to uncover trends, predict outcomes, automate tasks, and support decision-making in the legal industry. Legal data scientists often work with law firms, corporations, or government agencies to improve efficiency and gain insights from complex legal datasets.

What are the key skills and qualifications needed to thrive as a Legal Data Scientist, and why are they important?

To thrive as a Legal Data Scientist, you need a strong background in data analysis, statistics, and legal principles, often supported by degrees in law, computer science, or related fields. Familiarity with programming languages like Python or R, machine learning frameworks, and legal research databases is typically required. Excellent analytical thinking, attention to detail, and effective communication skills are crucial for interpreting complex legal data and collaborating with legal professionals. These skills enable you to extract valuable insights from legal datasets, drive data-informed decisions, and support compliance and litigation strategies.

What is the difference between Legal Data Science vs Legal Analyst?

AspectLegal Data ScienceLegal Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; knowledge of legal conceptsLegal degree or paralegal certification; understanding of legal procedures
Work EnvironmentData-driven teams, tech-focused settings, law firms, or legal departmentsLaw firms, corporate legal departments, courts
Employer & Industry UsageLegal tech companies, law firms, corporate legal teamsLaw firms, government agencies, corporate legal departments
Common Search & ComparisonLegal Data Science vs Legal Analyst

Legal Data Science focuses on analyzing large legal datasets using data science techniques, while Legal Analysts interpret legal information and support casework. Both roles are essential in legal settings but differ in technical skills and focus areas.

What are some common challenges faced by professionals in Legal Data Science roles?

Professionals in Legal Data Science often face challenges related to data quality and accessibility, as legal data is typically unstructured, sensitive, and dispersed across multiple sources. Navigating privacy regulations, ensuring data security, and maintaining confidentiality are critical aspects of the job. Additionally, legal data scientists must bridge the gap between legal teams and technical stakeholders, translating complex legal requirements into actionable data solutions. Effective collaboration and strong communication skills are essential to address these challenges and drive successful outcomes.
More about Legal Data Science jobs
What cities are hiring for Legal Data Science jobs? Cities with the most Legal Data Science job openings:
Infographic showing various Legal Data Science job openings in the United States as of June 2026, with employment types broken down into 79% Full Time, 5% Part Time, 5% Temporary, and 11% Contract. Highlights an 78% In-person, 11% Hybrid, and 11% Remote job distribution, with an average salary of $53,278 per year, or $25.6 per hour.
Senior Applied Scientist

Senior Applied Scientist

Relativity

Little Rock, AR โ€ข On-site, Remote

Other

Medical, Retirement

Posted 17 days ago


Job description

Posting Type

Remote/Hybrid

Job Overview

WHO WE ARE
Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy, trust, and accountability are critical.
Every year, the global justice system benefits from insights generated by Relativity AI across billions of documents. We are just getting started on our journey to use AI to improve the outcome of every discovery, investigation, and analysis performed on our platform.
At Relativity, we develop AI guided by our AI Principles. These principles ensure we build AI with clear purpose, empower customers with transparency and control, treat fairness and privacy as first principles, protect customer data by design, and act with a high standard of responsibility and accountability.
WHAT WE DO
Relativity's AI organization is focused on exploration, experimentation, and turning cutting-edge research into real-world impact. We believe innovation requires experimentation, learning, and iteration. Our teams experiment, evaluate, ship, and learn continuously while maintaining a strong commitment to responsible AI.
Applied Science Team
The Applied Science team operates at the core of Relativity's AI development. Our team includes specialists with advanced postgraduate training and deep experience building and operating machine learning models at scale. We work closely with engineering, product, design, data engineering, machine learning operations, and LLM engineering teams to translate complex AI research into production-ready features used by legal professionals around the world.

Job Description and Requirements

ABOUT THE ROLE

As a Senior Applied Scientist, Generative AI, you will design, build, and deploy generative and machine learning models that power Relativity's next generation of AI-driven product capabilities. You will collaborate closely with applied scientists, engineers, product managers, and designers to build models that help legal professionals organize data, discover the truth, and act on it with confidence.

This role balances research, development, and operational responsibility. You will contribute to Relativity's portfolio of transformational generative AI technologies while adhering to our responsible AI principles and ensuring models perform reliably in real-world, high-stakes environments.

WHAT YOU'LL DO

  • Develop machine learning and generative AI models that ship as customer-facing product features
  • Collaborate closely with engineers to write production-quality code and contribute across the full model deployment lifecycle
  • Design and evaluate models that operate at very large scale, including search and retrieval systems spanning hundreds of millions to billions of documents
  • Contribute to internal standards, processes, and tooling for building, evaluating, and deploying generative AI systems
  • Partner with Product and Data teams to assemble, curate, and synthesize datasets for model development and evaluation
  • Conduct rigorous experimentation, model evaluation, and iteration to improve model quality, explainability, safety, and performance
  • Collaborate across AI, engineering, and product teams to ensure models integrate effectively into larger systems
  • Apply Relativity's AI Principles to ensure responsible, fair, secure, and transparent AI development
  • Communicate complex data science and machine learning concepts clearly and effectively to collaborators with diverse technical backgrounds

WHAT WE'RE LOOKING FOR

Required

  • Experience building search or retrieval systems operating at the scale of hundreds of millions of documents
  • Experience developing and applying generative AI models as part of larger, domain-specific systems
  • Experience across the full machine learning lifecycle, including experimentation, evaluation, deployment, and iteration
  • Experience working in containerized environments using Kubernetes-based tooling and workflows
  • Interest in or experience with the legal industry, eDiscovery, or the broader justice system
  • Strong programming ability in a language such as Python
  • Comfort working in UNIX-based environments using command-line tools
  • Ability to communicate complex data science concepts thoughtfully and inclusively to a wide range of stakeholders

Preferred

  • Master's degree in Computer Science or a quantitative field plus 2 years of relevant industry experience
  • OR Ph.D. in Computer Science or a quantitative field
  • OR the equivalent of 5 years of relevant academic and/or industry experience
  • Experience building and deploying systems that leverage large language models
  • Experience contributing to shared data science or ML engineering standards, tooling, or best practices

WHY WE COULD BE A GREAT FIT

Impactful Mission

  • Your work directly contributes to improving outcomes across the global justice system by helping customers uncover critical insights in massive, complex datasets.

AI at Real Scale

  • You'll work on some of the largest and most complex AI systems in the legal technology market, operating at significant data and computational scale.

Growth and Collaboration

  • You'll collaborate closely with experienced applied scientists, engineers, and product leaders while continuing to grow your expertise in generative AI and production machine learning systems.

Responsible AI Culture

  • You'll be part of an organization deeply committed to building AI that is ethical, transparent, secure, and accountable.

Inclusive Environment

  • We value diverse perspectives, backgrounds, and ways of thinking, and believe they make our teams and products stronger.

Compensation and Benefits

  • Competitive compensation, health and retirement benefits, discretionary time off (DTO), parental leave for primary and secondary caregivers, company-wide breaks, wellness resources, and an equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$146,000 and $218,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Algorithms, C++ Programming Language, Computer Vision, Data Science, Deep Learning, Machine Learning (ML), Natural Language, Python (Programming Language), Researching, Statistical Models