83 Senior Data Scientist Jobs in Raleigh, NC
Slesha is Hiring a Senior Data Scientist Near Raleigh, NC
Role Description
This is a full-time Senior Data Scientist role at Slesha Inc. As a Senior Data Scientist, you will be responsible for performing data analysis, data visualization, and data analytics tasks on a daily basis. This is a hybrid role, based in Raleigh, NC, with the flexibility for some remote work.
The Senior Data Scientist will focus on search and be dedicated to the creation of next-generation AI and Machine
Learning techniques and strategies for LexisNexis in their global expansion. 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.
Top Skills:
- Master& or PhD Preferred
- 3-10 years of experience in AI and machine learning, model building and strong coding skills in python
- 2 years of working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc. UTILIZING
RAG!
- Experience working directly with large language models and Transformer based architectures including BERT,
RoBERTa, T5 etc.
- Experience with conversational search / semantic search, reinforcement learning, prompt engineering, hallucination
mitigation
- DevOps repos Debugging, building APIs and managing the algorithm flow across multiple workstreams in one repo
- Senior level experience deploying models in the Cloud (AWS) or Azure as secondary.
Nice to have: Candidate local to Raleigh is strongly preferred (hybrid schedule 2x per week)
- FANG Experience (Facebook, Amazon, Netflix, Google, or even Microsoft)
Qualifications
Strong coding skills in Python 7 years
Be a natural problem solver, able to take a lead in collaborating to resolve issues
Proficiency in IDE debugging : VSCODE and PYCHARM
Have communication skills
4 years of experience in AI and machine learning
Deep understanding of machine learning algorithms, classification models, diagnostic testing of models
Experience working directly and Transformer based architectures including BERT, RoBERTa, T5 etc. Nd familiarity with
large language models and fine tuning
Experience with conversational search / semantic search, reinforcement learning, prompt engineering, hallucination
mitigation
Working understanding of the business risks associated with applying LLM (LangChain) in a business
- Experience working with AWS, RAG, SageMaker, SQL
Job Summary
Full Time
$106k-131k (estimate)
06/23/2024
12/18/2024
slesha.com
Irving, TX
Related Companies
The job skills required for Senior Data Scientist include Machine Learning, Python, Algorithms, SQL, Data Analysis, Data Analytics, etc. Having related job skills and expertise will give you an advantage when applying to be a Senior Data Scientist. That makes you unique and can impact how much salary you can get paid. Below are job openings related to skills required by Senior Data Scientist. Select any job title you are interested in and start to search job requirements.
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Quotes from people on Senior Data Scientist job description and responsibilities
Senior Data Scientists rae responsible in formulating, suggesting, and managing data-driven projects which are geared at furthering the business's interests.
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Collating and cleaning data from various entities for later use by junior data scientists.
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Delegating tasks to Junior Data Scientists in order to realize the successful completion of projects.
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They also monitor the performance of Junior Data Scientists and providing them with practical guidance, as needed.
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May also be tasked in selecting and employing advanced statistical procedures to obtain actionable insights.
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Career tips from people on Senior Data Scientist jobs
Present final result to stakeholders. Make adjustments based on feedback.
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Learn the required skills to become a data scientist.
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Review additional data scientist certifications and post-graduate learning.
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Ask the right questions to begin the discovery process.
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Choose one or more potential models and algorithms.
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