Manager Data Science**Home based San Francisco, CA

Archer; San Francisco (CA); On-site; USD 115,000 - 192,000; Full time

Job summary

Archer, in partnership with LexisNexis, is seeking a Manager Data Science to lead a team of junior data scientists and drive advanced ML initiatives.

You will guide model development, oversee training and evaluation, mentor staff, and collaborate with product and engineering to deploy reliable AI solutions.

The role offers a competitive US base pay range, flexible working patterns, annual incentive eligibility, and country-specific benefits.

Qualifications

• Strong understanding of transformer architectures, attention mechanisms, tokenization, language modeling objectives.
• Proficiency in Python and PyTorch with experience in Hugging Face tools.
• Hands-on experience with supervised fine-tuning (SFT) and loss masking; model checkpointing.
• Familiarity with parameter-efficient fine-tuning (PEFT) such as LoRA/QLoRA.
• Ability to build instruction-response datasets and manage data leakage risks.
• Experience with distributed training and multi-GPU setups.

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.

Skills

LLM Fundamentals

Python

PyTorch

Hugging Face

Fine-tuning

PEFT

Tools

Transformers (Hugging Face)

Job description

Archer is collaborating with LexisNexis to connect them with exceptional professionals for this role.

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.

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.

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.

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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