Manager Data Science*Home based San Francisco, CA

LexisNexis Legal & Professional group; United States; Remote; USD 115.000 - 192.000; Vollzeit

Benefits dieser Stelle

Parental leave

Study assistance

Sabbaticals

Zusammenfassung

LexisNexis Legal & Professional is seeking a Manager Data Science to lead a team of junior data scientists in the design, training, and evaluation of large language models tailored to business and legal applications.

You will guide best practices, supervise data preparation, and work with product and engineering to deploy models that improve decision-making and analytics capabilities across the organization.

Qualifikationen

• Strong understanding of transformer architectures and language modeling objectives.
• Experience implementing supervised fine-tuning (SFT) and PEFT methods.
• Experience training models on multi-GPU clusters and managing training pipelines.

Aufgaben

• Lead the design and execution of LLM training and fine-tuning projects.
• Oversee preparation of high-quality training datasets (collection, cleaning, annotation).
• Develop and optimize SFT/PEFT workflows and tuning strategies.
• Establish evaluation frameworks for accuracy, safety, and domain relevance.
• Diagnose training issues and improve model quality and efficiency.
• Mentor data scientists and enforce reproducible development practices.
• Partner with product/engineering to define requirements and deployment plans.
• Manage project priorities, timelines, and compute resources.

Kenntnisse

LLM fundamentals

Python

PyTorch

Hugging Face

SFT training

PEFT fine-tuning

GPU training

Experiment tracking

Tools

PyTorch

DeepSpeed

Hugging Face Transformers

Jobbeschreibung

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

• 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.

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.

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.