Senior Data Scientist

1 month ago

Raleigh, United States Mastech Digital Full time

Role: Senior Data Scientist

Location: Raleigh, NC- Hybrid is needed

Long term role


W2 role only..


Must Have:

• Gen AI/LLM experience

• Masters and/or PHD



Top Skills' Details:

• 5-7+ years of experience in AI and machine learning, model building and strong coding skills in python

• Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.

• DevOps repos Debugging, building APIs and managing the algorithm flow across multiple workstreams in one repo

• Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.

• Senior level experience deploying models in the Cloud (AWS)


Nice to Have:

• French Bilingual


Job Description:

• Needs to hire a Senior Data Scientist for their flagship product, LexisNexis® Legal & Professional, a leading global provider of information and analytics.

• Recently Client has focused on the general availability of Lexis+ AI™ for U.S. customers, a generative AI solution designed to transform legal work. Lexis+ AI delivers trusted results in a familiar, easy-to-use interface with linked hallucination-free legal citations that combine the power of generative AI with proprietary search technology, Shepard’s® Citations functionality, and authoritative content.

• The Senior Data Scientist will focus on search and be dedicated to the creation of next-generation AI and Machine Learning techniques and strategies.

• This candidate will assist with deploying ethical, powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model for each individual legal use case.

• This approach includes working with large language models like Anthropic’s Claude 2, hosted on Amazon Bedrock from Amazon Web Services (AWS), and OpenAI’s GPT-4 and ChatGPT, hosted on Microsoft Azure.


Accountabilities:

• Solve some of the most challenging problems in natural language processing, machine learning, and information retrieval including topical classification, sentiment analysis, user intent detection.

• Research, build, and deploy models based on both shallow and deep machine learning. Train robust NLP-based models a very large corpus of news and financial data.

• Apply machine learning techniques for improving search algorithms.

• Drive best practices for NLP/Machine Learning pipelines.

• Maintain current knowledge base of state-of-the-art ML algorithms (BERT, ELMo, GPT, etc.), API's, and open-source methods and be able to quickly evaluate alternatives.

• Translate complex business requirements into actionable stories with reasonable time estimates.

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