Logo for RELX

Manager Data Science**Home based San Francisco, CA

Role overview

Qualifications

  • Strong understanding of transformer architectures, attention mechanisms, tokenization, language modeling objectives, and the differences between pretraining, continued pretraining, and fine-tuning.
  • Strong Python and PyTorch skills, with practical experience using Hugging Face Transformers, Datasets, or equivalent tools.
  • Demonstrated ability to implement supervised fine-tuning (SFT), configure training objectives and loss masking, tune hyperparameters, and select model checkpoints.
  • Experience training models across multiple GPUs using frameworks such as PyTorch FSDP or DeepSpeed.

Responsibilities

  • Lead the design and execution of LLM training and fine-tuning projects, including model selection, training strategy, experimentation, and evaluation.
  • Oversee the preparation of high-quality training datasets, including data collection, cleaning, deduplication, annotation, and quality validation.
  • Develop and optimize supervised fine-tuning and parameter-efficient fine-tuning workflows; apply preference optimization methods where appropriate.
  • Manage and mentor data scientists, review technical work, and establish reproducible development practices.

Key facts

Hard skills

Other skills

  • Team Leadership
  • Communication
  • Mentorship

About the company

RELX logo

RELX

Information Services & Data Providers

RELX is a global provider of information-based analytics for professional and business customers across industries.We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions.In short, we enable our customers to make better decisions, get better results and be more productive.We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America.We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.____Please note that RELX does not contact people through social media to extend job or contract offers, nor do we request money, credit card details or bank account information as part of any project or job application process. Any such request is fraudulent. Please contact your local law enforcement agency if you have been victimized by a scammer. For careers, access https://www.relx.com/careers/why-relx

Company details

Company typeXLarge
IndustryInformation Services & Data Providers
Company size10001

Your match analysis

See how your profile stacks up against this role.

We compared the job requirements to your profile to show where you're strong and where you fall short.

Job description

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.


About the Role


A Manager Data Science is an emerging subject matter expert in their domain. They lead a team of junior members to support their development and work product. They are mindful of best practices and train their team in the execution of those best practices. They manage a team to define new best practices and innovative approaches to new business problems or use cases.

Responsibilities


  • Lead the design and execution of LLM training and fine-tuning projects, including model selection, training strategy, experimentation, and evaluation.
  • Oversee the preparation of high-quality training datasets, including data collection, cleaning, deduplication, annotation, and quality validation.
  • Develop and optimize supervised fine-tuning and parameter-efficient fine-tuning workflows; apply preference optimization methods where appropriate.
  • Establish evaluation frameworks to assess factual accuracy, instruction following, domain relevance, safety, and performance on business-specific tasks.
  • Diagnose training issues and improve model quality, training stability, GPU utilization, and computational efficiency.
  • Manage and mentor data scientists, review technical work, and establish reproducible development practices.
  • Partner with product, engineering, and domain experts to define requirements and support model deployment and monitoring.
  • Manage project priorities, timelines, and compute resources, and communicate results and tradeoffs to stakeholders.

Requirements


  • LLM fundamentals: Strong understanding of transformer architectures, attention mechanisms, tokenization, language modeling objectives, and the differences between pretraining, continued pretraining, and fine-tuning.
  • Programming and frameworks: Strong Python and PyTorch skills, with practical experience using Hugging Face Transformers, Datasets, or equivalent tools.
  • Hands-on LLM training: Demonstrated ability to implement supervised fine-tuning (SFT), configure training objectives and loss masking, tune hyperparameters, and select model checkpoints.
  • Efficient fine-tuning: Practical experience with parameter-efficient fine-tuning (PEFT), including LoRA or QLoRA, and an understanding of their quality, memory, and compute tradeoffs.
  • Training data engineering: Ability to build instruction-response datasets, apply chat templates, manage sequence lengths and packing, and prevent data leakage and evaluation contamination.
  • GPU and distributed training: Experience training models across multiple GPUs using frameworks such as PyTorch FSDP or DeepSpeed, including mixed precision, gradient accumulation, and gradient checkpointing.
  • Evaluation and debugging: Ability to design reliable benchmarks and human evaluations, analyze model errors, and troubleshoot unstable loss, overfitting, and GPU memory issues.
  • Reproducibility: Experience with experiment tracking, dataset and model versioning, checkpoint management, and documented training pipelines.

Work in a Way That Works for You


We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.


Working Pattern


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.

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.




U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.



This job is eligible for an annual incentive bonus.







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.

Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here.

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.

USA Job Seekers:

EEO Know Your Rights.

Apply once. Then go straight to the hiring manager.

After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.

MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
Unlocked after you apply
·

Related jobs

Other jobs at RELX

Premium

Reach out to the hiring manager directly.

Gain access to the contact details of the hiring managers who actually decide, and reach out to network with them directly. That, plus more when you upgrade:

  • Full match report with fit score and gaps
  • Career diagnostics on how recruiters read you
  • Curated company matches and warm intros
  • 48h early access to new roles

Cancel anytime.