Develop regression and classification models using established and emerging data science methodologies
Chain, fine-tune and deploy pre-trained language models (e.g., BERT, Llama, Qwen, etc.) to optimize performance on a range of NLP tasks, including text classification, named entity recognition, and generative tasks such as summarization, clause and document generation, and question-answer exchanges
Design and deploy document segmentation and embedding approaches to facilitate information retrieval and retrieval augmented generation (RAG)
Conduct advanced quantitative research, using machine learning (ML) and natural language processing (NLP) techniques to understand patterns in large volumes of data, identify relationships, detect data anomalies and classify data
Configure practice-specific AI workflows and language technologies, which may require complex pipelines, prompt engineering, prompt chaining, and text operations
Design and deploy highly visual reports and user interfaces that surface quantitative insights in forms that are fit-for-purpose, modern and easily accessible to non-technical business professionals
Stay current with the latest advancements in LLMs, NLP, deep learning and ML research, implementing cutting-edge techniques and incorporating them into production models as appropriate
Document development processes, codebase, and best practices to facilitate knowledge sharing and maintain a well-organized, reproducible environment
Partner with other technical resources to refine data pipelines for recurring classes of analysis and data-driven solutions
Handle projects on request under the direction of the CKIO and other executive staff
Education
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 a significant plus
Skills and Experience
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 a plus
Solid understanding of deep learning frameworks such as TensorFlow or PyTorch 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
Salary Information
NY Only: The estimated base salary range for this position is $150,000 to $175,000 at the time of posting.
The actual salary offered will depend on a variety of factors, including without limitation, the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location in which the applicant lives and/or from which they will be performing the job. This role is exempt meaning it is not overtime pay eligible.
Simpson Thacher will not sponsor applicants for work visas for this position.
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