Enterprise Data Scientist

Location: Richmond, VA

Duration: Permanent

Responsibilities:

• Develop the AI/ML strategy and roadmap driving organizational AI maturity to transformational state.
• Develop and own Responsible and Ethical AI guidelines for all embedded and custom developed models across the organization.
• Lead data science initiatives developing, deploying and maintaining predictive and prescriptive solutions using AI/ML and other advanced analytics modeling techniques.
• Develop and lead MLOps model life cycle management practice.
• Work with structured, semi-structured and unstructured clinical data to develop NLP/GenAI/LLM based tools and solutions for clinicians advancing patient care.
• Develop procedures and tools to audit and analyze model’s performance and accuracy.
• Collaborate with clinicians, researchers and other stakeholders to understand domain-specific requirements and translate them into computational solutions.
• Develop AI/ML based automation solutions that optimize business workflows and processes.
• Stay updated with the latest advancements in deep learning neural networks techniques and technologies to ensure the models developed are state-of-the-art.
• Design and maintain a curriculum for coaching and training current and prospective end users to better understand how these tools can enhance business decision making capabilities.
• Mentoring and Training other Data Science team members on best practices and technologies
• Required Education: Master’s degree in applied mathematics, computer science, engineering, statistics, or a related field required.
• Years and Type of Required Experience: 7+ years’ experience in Machine Learning/Artificial Intelligence tools and technologies required. 7+ years’ experience in Python or R and SQL required. 5+ years’ experience in Healthcare environment
• Other Knowledge, Skills and Abilities Required: Experience working with unstructured data and big data is required. Experience working with one of the opensource ML libraries/frameworks -PyTorch/TensorFlow/Keras/Numpy required. Experience with Foundation models, fine-tuning or RAG required. Knowledge of Data Management, BI, Data Warehousing, ETL and Data Governance concepts preferred. Experience working with Cloud technologies such as AWS/Azure/GCP required.
• Other Knowledge, Skills and Abilities Preferred: Displays intellectual curiosity and integrity. 5+ years in Healthcare Environment
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