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About the Role
Simpson Thacher's Data Scientist will leverage statistics, machine learning, deep learning, and natural language processing to deliver insights to leadership, legal practices, and administrative functions. This role is key to advancing the Firm's AI initiatives and involves working on advanced projects within the legal industry. The position requires creative problem-solving, analytical rigor, technical skill, and an understanding of the legal field.
Responsibilities
- Support legal teams and operational staff in using data for decision-making and improving efficiency.
- Collaborate with Firm departments to analyze data and develop solutions for operational objectives.
- Develop regression and classification models using established and emerging data science methodologies.
- Chain, fine-tune, and deploy pre-trained language models for NLP tasks like text classification, named entity recognition, and generative tasks.
- Design and deploy document segmentation and embedding approaches for information retrieval and RAG.
- Conduct advanced quantitative research using ML and NLP to understand data patterns, identify relationships, detect anomalies, and classify data.
- Configure practice-specific AI workflows and language technologies, including complex pipelines, prompt engineering, and text operations.
- Design and deploy visual reports and user interfaces to present quantitative insights to non-technical professionals.
- Stay current with advancements in LLMs, NLP, deep learning, and ML research, implementing cutting-edge techniques.
- Document development processes, codebase, and best practices for knowledge sharing and reproducibility.
- Partner with technical resources to refine data pipelines for recurring analyses and data-driven solutions.
- Handle projects as directed by executive staff.
Requirements
- A bachelor’s degree required, preferably in data science, mathematics, statistics, computer science, engineering, finance or a related field.
- Master’s degree in data science, computer science, statistics, computational linguistics or engineering preferred.
- Prior coursework in deep learning, natural language processing, or information retrieval is a significant plus.
- 2+ years in a data science, machine learning engineering, artificial intelligence or equivalent role, or a PhD in a related field.
- Highly proficient with statistical programming (e.g., Python, R) and databases (e.g., SQL, Pinecone).
- Proven experience developing and validating linear and non-linear regression and classification models.
- Expertise in data transformation, data science and visualization libraries (e.g., pandas, scikit-learn, matplotlib, Seaborn).
- Experience with natural language processing and related libraries (e.g., Hugging Face’s Transformers, spaCy, NLTK) preferred.
- Ability to design and develop object-oriented machine learning systems beyond Jupyter notebooks is a plus.
- Solid understanding of deep learning frameworks such as TensorFlow or PyTorch is a plus.
- Proficiency with version control systems such as Git or equivalent tools for code management and collaboration.
- Able to translate business problems to technical logic and practical solutions.
- Able to communicate complex results clearly to a non-technical audience.
- Proactively develops and maintains technical knowledge in emerging data science areas.
- Experience in the legal field is a significant plus.
- Will not sponsor applicants for work visas.
Skills
- Statistics
- Machine Learning
- Deep Learning
- Natural Language Processing (NLP)
- Python
- R
- SQL
- Pinecone
- Linear Regression
- Non-linear Regression
- Classification Models
- pandas
- scikit-learn
- matplotlib
- Seaborn
- Hugging Face’s Transformers
- spaCy
- NLTK
- Object-Oriented Machine Learning Systems
- TensorFlow
- PyTorch
- Git
- Prompt Engineering
- Prompt Chaining
- Text Operations
- Document Segmentation
- Embedding Approaches
- Information Retrieval
- Retrieval Augmented Generation (RAG)
- AI Workflows
- Language Technologies
- Data Visualization
- Quantitative Research
- Data Transformation
Location
- New York
Work Type
- Hybrid
Experience Level
- 2+ years of experience in a data science, machine learning engineering, artificial intelligence or equivalent role, or a PhD in a related field.
Education Level
- Bachelor's degree in data science, mathematics, statistics, computer science, engineering, finance or a related field
- Master's degree in data science, computer science, statistics, computational linguistics or engineering preferred
- Prior coursework in deep learning, natural language processing, or information retrieval a significant plus
Salary/Compensations
- $150,000 to $175,000
About the Company
- Simpson Thacher & Bartlett LLP is committed to a collegial work environment in which all individuals are treated with respect and dignity.
Equal Opportunity
- The Firm prohibits discrimination or harassment based upon race, color, religion, gender, gender identity or expression, age, national origin, citizenship status, disability, marital or partnership status, sexual orientation, veteran’s status or any other legally protected status.
- This Policy pertains to every aspect of an individual’s relationship with the Firm, including but not limited to recruitment, hiring, compensation, benefits, training and development, promotion, transfer, discipline, termination, and all other privileges, terms and conditions of employment.