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Data Scientist

3 months ago

Providence, United States Omni Inclusive Full time
  • A solid foundation in Python programming is essential, along with familiarity with popular AI libraries/frameworks such as Langchain, TensorFlow, PyTorch, scikit-learn, and spaCy.
  • Demonstrated proficiency in developing AI solutions using Azure services, including Azure AI Search, Azure OpenAI APIs, and Azure SQL Database.
  • In-depth knowledge of search algorithms, indexing techniques, and retrieval models for effective information retrieval tasks. Familiarity with search platforms like Elasticsearch or Azure AI Search is highly advantageous.
  • Hands-on experience with RAG architecture and its application in natural language processing tasks is a must.
  • Ability to proficiently manipulate data, perform complex queries, and conduct data transformations using SQL Server.
  • A solid understanding of machine learning and deep learning techniques, particularly those relevant to natural language processing tasks such as text extraction, text classification, sentiment analysis, named entity recognition, and summarization.
  • Ability to preprocess and clean large datasets efficiently using SQL/Python and other data manipulation tools. Experience with techniques such as data normalization, feature engineering, and data augmentation is preferred.
  • Expertise in working with healthcare data standards (ex. HIP nd FHIR), sensitive data and data masking techniques to mask personally identifiable information (PII) and protected health information (PHI) is essential.
  • Knowledge of cloud computing principles and experience in deploying, scaling, and monitoring AI solutions on cloud platforms like Azure.
  • Ability to communicate complex technical concepts effectively to technical and non-technical stakeholders and collaborate with cross-functional teams.
  • Analytical mindset with a keen attention to detail, coupled with the ability to solve complex problems efficiently.
  • Knowledge of cloud cost management principles and best practices to optimize cloud resource usage and minimize costs.
Must Have:
  • Minimum of 10 years' experience as a data scientist.
  • Deep hands-on experience using Python.
  • Hands-on experience scaling POC to production
  • Hands-on experience with Azure Cloud eco-system
  • Hands-on experience using tools such as Document Intelligence (formerly Azure Form Recognizer), Snowflake, Azure AI Search, Azure OpenAI
  • Experience working with PII/PHI
  • Hands-on experience working with unstructured data.
  • Must have implemented a use case using RAG architecture.