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About This Role
About our Team:
LexisNexis Legal \& Professional, serving customers in over 150 countries with 11,800 employees worldwide, is part of RELX, a global provider of information\-based analytics and decision tools for professional and business customers. Our company is a leader in deploying AI and advanced technologies to improve productivity and transform the legal market. We prioritize using the best models from today's top creators for each legal use case.
About the Role:
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We are seeking a Senior Data Scientist II to help lead the design and validation of Agentic AI\-driven product capabilities within the legal domain.
This role focuses on defining *what to build and why* —leveraging machine learning, NLP, and large language models (LLMs) to solve complex legal workflows. You will help drive experimentation, modeling, and evaluation, partnering closely with engineers to translate validated approaches into scalable, customer\-facing solutions.
Responsibilities:
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- Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).
- Define agentic workflows and reasoning strategies for multi\-step legal tasks.
- Develop retrieval strategies, including hybrid search (semantic \+ lexical), and evaluation metrics (e.g., relevance, ranking quality).
- Analyze large\-scale legal datasets to extract insights and improve model performance.
- Establish best practices for model evaluation, validation, and benchmarking.
- Translate experimental results into clear product recommendations and business impact.
- Collaborate with product, legal experts, and engineers to align solutions with user needs.
- Mentor team members and provide technical leadership in data science and AI.
Requirements:
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- Education: Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).
- Strong experience in machine learning, NLP, and LLM\-based modeling.
- Strong experience designing and running experiments, including model evaluation and iteration.
- Strong coding skills.
- Experience with generative AI techniques (e.g., prompt engineering, RAG).
- Experience designing and evaluating hybrid search (semantic \+ lexical) using embeddings and vector databases.
- Experience designing agentic workflows and reasoning strategies, with hands\-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real\-world use cases.
- Proficiency in Python and data analysis tools.
- Strong foundation in statistics, modeling, and large\-scale text processing.
Work in a way that works for you
We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous well\-being initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long\-term goals.
- Working flexible hours \- flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
Working for you
We know that your well\-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
- Health Benefits: Comprehensive, multi\-carrier program for medical, dental and vision benefits
- Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
- Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time\-off Programs
- Short\-and\-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
- Family Benefits, including bonding and family care leaves, adoption, and surrogacy benefits
- Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
- Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice
About the Business
LexisNexis Legal \& Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision\-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.
\#AIFluency
U.S. National Base Pay Range: $104,900 \- $174,700\. Geographic differentials may apply in some locations to better reflect local market rates.If performed in Colorado, the base pay range is $104,900 \- $174,700\.If performed in Illinois, the base pay range is $110,100 \- $183,500\.If performed in Chicago, IL, the base pay range is $115,400 \- $192,200\.If performed in Maryland, the base pay range is $110,100 \- $183,500\.If performed in New York, the base pay range is $115,400 \- $192,200\.If performed in New York City, the base pay range is $125,900 \- $209,700\.If performed in Rochester, NY, the base pay range is $104,900 \- $174,700\.If performed in New Jersey, the base pay range is $123,816 \- $197,784\.If performed in Ohio, the base pay range is $99,700 \- $166,000\.This job is eligible for an annual incentive bonus.Application deadline is 07/31/2026\.
We know your well\-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1\-855\-833\-5120\.
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Please read our Candidate Privacy Policy .
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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Salary Context
This $104K-$174K range is below the median for Data Scientist roles in our dataset (median: $155K across 226 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At RELX Group, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($139K) sits 28% below the category median. Disclosed range: $104K to $174K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
RELX Group AI Hiring
RELX Group has 4 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Philadelphia, PA, US, Raleigh, NC, US, Alpharetta, GA, US. Compensation range: $148K - $174K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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