Manager Data Science*Home based San Francisco, CA

LexisNexis Risk Solutions; San Francisco (CA); Hybrid; USD 115,000 - 192,000; Full time

Benefits offered by this job

Annual incentive bonus

Country-specific benefits

Wellbeing initiatives

Shared parental leave

Study assistance

Sabbaticals

Job summary

LexisNexis Risk Solutions is seeking a Manager Data Science to lead a team of junior data scientists, set best practices, and partner with product and engineering to deploy models.

You will supervise LLM training, data curation, evaluation, and scalable workflows with a focus on accuracy, efficiency, and maintainability.

Qualifications

• Experience with LLMs, transformers, and language modeling objectives.
• Strong Python and PyTorch skills with Hugging Face tooling.
• Experience with supervised fine-tuning (SFT) and parameter-efficient fine-tuning (PEFT).
• Experience with multi-GPU training and distributed training frameworks.

Responsibilities

• Lead design and execution of LLM training and fine-tuning projects.
• Oversee high-quality training data preparation and validation.
• Develop and optimize fine-tuning workflows (PEFT/LoRA/QLoRA).
• Establish evaluation frameworks for factual accuracy and safety.

Skills

LLM fundamentals

Python

PyTorch

Hugging Face

SFT

PEFT

Data engineering

GPU training

Experiment design

Experiment tracking

Tools

Hugging Face Transformers

DeepSpeed

PyTorch FSDP

QLoRA

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.

Salary & Benefits

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.

Commitment to Accessibility

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.

Privacy Notice

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Equal Opportunity Employer

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.

Company Vision

LexisNexis Legal & Professional is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision‑making and outcomes, and advance the rule of law across the world. We help lawyers win cases, manage their work more efficiently, serve their clients better and grow their practices. We assist corporations in better understanding their markets and preventing bribery and corruption within their supply chains. We partner with leading global associations and customers to help collect evidence against war criminals and provide tools to combat human trafficking. We endeavour to advance the rule of law across the world.Our teams are combining unparalleled legal and business information with analytics and technology to advance what’s possible for the way our customers work and to advance what’s possible in the world by strengthening the rule of law.