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Legal Data Science Jobs (NOW HIRING)

Overview The VP, Marketing Data Science is a highly experienced and senior role, part of the larger ... Extensive experience working closely with legal, compliance and procurement teams on technology ...

Senior Software Engineer

Chicago, IL

$126K - $166K/yr

Apply data science methodologies including statistical analysis, predictive modeling, and machine learning to legal data for insights and automation. * Monitor performance, usage, and compliance of ...

Senior Analyst, Data Science

Fort Mill, SC · On-site

$75K - $95K/yr

... Legal, and Risk . This role sits on a small, high-leverage data science team within our Data Analytics & Reporting organization, chartered to deliver trusted, AI-enabled insights that drive ...

WI · On-site

Job Overview Relativity is a leading legal data intelligence company building AI technology that ... Bachelor's degree in Business, Computer Science, Engineering, or Design, or comparable work ...

New

Senior Analyst, Data Science

Fort Mill, SC · On-site

$75K - $95K/yr

... Legal, and Risk . This role sits on a small, high-leverage data science team within our Data Analytics & Reporting organization, chartered to deliver trusted, AI-enabled insights that drive ...

Showing results 41-60

Legal Data Science information

See salary details

$27.5K

$53.3K

$85K

How much do legal data science jobs pay per year?

As of Aug 20, 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 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.

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.

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 August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $53,278 per year, or $25.6 per hour.

VP Marketing Data Science

Citigroup Inc.

Manhattan, NY • On-site

$140 - $180/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 20 days ago


Citibank rating

8.3

Company rating: 8.3 out of 10

Based on 177 frontline employees who took The Breakroom Quiz

39th of 171 rated banks


Job description

Overview

The VP, Marketing Data Science is a highly experienced and senior role, part of the larger Media Sciences team in the Client Org, reporting to the SVP Marketing Data Science.

This role will primarily perform advanced analytics on data from the clean room, marketing data analytics, audience analytics, creative analysis, consumer journey, attribution and scenario planning.

This pivotal role will be responsible for leading advanced analytics initiatives and developing sophisticated measurement models to optimize marketing spend and drive demonstrable business impact. The successful candidate will be a strategic thinker with deep expertise in data science, marketing analytics, and a proven track record of translating complex data into actionable insights for senior stakeholders.

Key Responsibilities
  • Design, develop, and implement advanced statistical and machine learning models to analyze marketing effectiveness, cross-channel attribution, audience analytics and user journey analytics.
  • Leverage multiple analytical approaches, tools and techniques on multiple data sources (media channel data, acquisitions data, revenue data, digital data) to conduct A/B testing and incrementality studies addressing business questions through a marketing lens.
  • Utilize predictive analytics to forecast marketing outcomes, identify optimal spending levels, and inform budget allocation decisions.
  • Translate complex business questions into analytical problems and guide the team in developing data‑driven solutions.
  • Communicate complex analytical concepts and data‑driven insights clearly to diverse audiences, including senior leadership, marketing teams and cross‑functional partners.
  • Oversee the end-to-end model development lifecycle, from data collection and preprocessing to model building, validation, and deployment.
  • Ensure the team adheres to best practices in data science, model governance and ethical data usage and ensure timely deployment of models.
  • Serve as a subject‑matter expert in analytics, drive ideation on analytical projects and simplify outcomes for stakeholders.
Qualifications
  • 6‑10 years of experience within media measurement and analytics, preferably in financial services, client side, agency side or publisher side.
  • Proficiency in Python and R and experience with relevant data science libraries and frameworks.
  • Experience with big data technologies, cloud platforms and data visualization tools such as SQL, Tableau, Power BI and Dataiku.
  • Hands‑on experience with complex structured and unstructured marketing data and leading predictive modeling using machine learning, deep learning and neural networks across multiple projects.
  • Strong understanding of core AI/ML concepts (RNN, LSTMs, LLMs, NLP) and ability to identify the optimal solution for any business case.
  • Ability to independently own and project‑manage workstreams involving multiple stakeholders, demonstrating accountability and decisiveness.
  • Ready for hands‑on involvement in measurement to identify roadblocks, uncover solutions, operate with curiosity and be hypothesis‑driven.
  • Process‑oriented, organized and able to deliver high‑quality work in a fast‑paced dynamic environment across teams.
  • Extensive experience working closely with legal, compliance and procurement teams on technology contracting and approvals in a highly regulated environment.
  • Tools and Platforms: proficient in Python/R, Hive/SQL; experience with machine learning frameworks like TensorFlow, PyTorch; good to have experience on Gen AI platforms and tools.
Education

Masters or Bachelor’s degree in Business Analytics, Finance, Statistics (advanced degree preferred).

Benefits

Citi offers competitive benefits including medical, dental and vision coverage; 401(k); life, accident and disability insurance; wellness programs; paid time off packages (vacation, sick leave, paid holidays). For additional information, please visit citibenefits.com.

Legal Notices

Citi is an equal opportunity employer and qualified candidates will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran or any other characteristic protected by law.

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What Citibank employees say

Pay

Benefits

Hours and flexibility

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About Citigroup Inc

Sourced by ZipRecruiter

We live in an increasingly complex world. Companies these days are either born global or are going global at record speed. Business and geopolitics are forging an entirely new dynamic and consumers now expect financial services to be a seamless part of their digital lives. Citi is a bank that’s uniquely positioned for this moment. Through our vast global network and our on-the-ground expertise, we can connect the dots, anticipate change and empathize the needs of our clients and customers in ways that other banks simply cannot. Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We have set expectations for how we must act to bring our mission to life. These expectations are at the heart of our Leadership Principles – we take ownership, we deliver with pride and we succeed together.

Industry

Banking and credit intermediation

Company size

5,001 - 10,000 Employees

Headquarters location

New York City, NY, US