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Manager Data Science**Home based San Francisco, CA

  • Remote
  • 6+ years

Salary

$115,400 - 192,300/ year

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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.

Responsibilit ies

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 product ive.
  • 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.
  • &xa;&xa;U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.&xa;&xa;&xa;&xa;This job is eligible for an annual incentive bonus.&xa;&xa;&xa;&xa;&xa;&xa;
  • 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 .
  • USA Job Seekers:

Where you’d work

Fully remote

About the company

RELX

Offices in San Francisco, United States, United States

Also hiring in Sydney, Australia, Australia, London, United Kingdom and 21 more places

9 of their 153 open roles are remote

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 21 checks run
  • 2 red flags

Still hiring?

14 checks

No red flags

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7 checks

2 red flags

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  • Must-haves
Details11 facts · Role, Location, Compensation, Employment
Tech stack
  • Python
  • PyTorch
  • LLMs
Seniority
Lead
Type
Full-time
Specialty
Data Science
Region
United States
Pay period
Annual
Show 5 more factsShow less

Role

Category
Data & Analytics
Specialty
Data Science
Seniority
Lead
Experience
6+ years
Tech stack
  • Python
  • PyTorch
  • LLMs

Location

Work model
Remote
Region
United States
Offices
  • San Francisco, United States
  • United States

Compensation

Salary
$115,400 - 192,300 / year
Pay period
Annual

Employment

Type
Full-time

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