Job Description
As a data scientist on our team, you will work on new product development in a small team environment writing production code in both run-time and build-time environments. You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets including matter and contract repository, invoice/legal spend data and work management. You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators. You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company.
Responsibilities
" Develop and implement LLM-based applications tailored for in-house legal
" Fine-tune and deploy large language models to enhance their performance on legal text processing tasks
" Evaluate and help maintain our data assets and training/evaluation data sets
" Design and build pipelines for preprocessing, annotating, and managing legal document datasets
" Collaborate with legal experts to understand requirements and ensure models meet domain-specific needs
" Conduct experiments and evaluate model performance to drive continuous improvements
" Interface with other technical personnel or team members to finalize requirements.
" Work closely with other development team members to understand moderately complex product requirements and translate them into software designs.
" Successfully implement development processes, coding best practices, and code reviews for production environments.
Requirements
" Formal training in machine learning: dimensionality reduction, clustering, embeddings, and sequence classification algorithms
" Experience with deep learning frameworks such as PyTorch, Tensorflow and Hugging Face Transformers.
" Practical experience in Natural Language Processing methods and libraries such as spaCy, word2vec, TensorFlow, Keras, PyTorch, Flair, BERT
" Practical experience with large language models, prompt engineering, fine-tuning and benchmarking, using frameworks such as LangChain and LlamaIndex
" Strong Python background
" Knowledge of AWS, GCP, Azure, or other cloud platform
" Understanding of data modeling principles and complex data models.
" Proficiency with relational and NoSQL databases as well as vector stores (e.g., Postgres, Elasticsearch/OpenSearch, ChromaDB)
" Knowledge of Scala, Spark, Ray, or other distributed computing systems highly preferred
" Knowledge of API development, containerization, and machine learning deployment highly preferred
" Experience with Client Ops/AI Ops highly preferred
Preferred Qualifications
" MS in Data Science, Computer Science, Statistics, Machine Learning, or related field
" 2+ years of relevant work experience
" Or undergraduate degree in relevant field and 4+ years of relevant work experience
Bachelor's degree