Netsmart - Senior Data Scientist - Generative AI

About the job : We are seeking a Senior Data Scientist - Gen AI with hands-on experience in building and deploying data-driven solutions. You will work closely with cross-functional teams to extract insights, develop machine learning models, and deploy scalable analytics solutions across various cloud platforms. As a Senior Data Scientist - Gen AI, you'll play a key role in harnessing data to drive better outcomes, improve performance, and enhance the lives of those served by our clients. Key Responsibilities : - The ability to design and develop ML, Gen AI, NLP, LLM Models for AI data pipelines. - Model components will include data ingestion, preprocessing, Retrieval Augmented Generation (RAG), NLP/LLM model development, fine-tuning and prompt engineering. - Analyze large, complex healthcare datasets including electronic health records (EHR) and claims data. - Develop statistical models for patient risk stratification, treatment optimization, population health management, and revenue cycle optimization. - Build models for clinical decision support, patient outcome prediction, care quality improvement, and revenue cycle optimization. - Create and maintain automated data pipelines for real-time analytics and reporting. - Work with healthcare data standards (HL7 FHIR, ICD-10, CPT, SNOMED CT) and ensure regulatory compliance. - Develop and deploy models in cloud environments while creating visualizations for stakeholders. - Present findings and recommendations to cross-functional teams including clinicians, product managers, and executives. Qualifications required : - Bachelor's degree in data science, Statistics, Computer Science, Mathematics, or related quantitative field. - 5 - 7 years of hands-on experience in data science, analytics, or machine learning roles. - Knowledge of ML Ops practices deploying and operationalize AI models. - Familiarity with cloud platforms (Azure, AWS, GCP) and containerized deployments (Docker, Kubernetes). - Demonstrated experience working with large datasets and statistical modeling. - Proficiency in Python or R for data analysis and machine learning. - Experience with SQL and database management systems. - Knowledge of machine learning frameworks such as scikit-learn, TensorFlow, PyTorch. - Familiarity with data visualization tools such as Tableau, Power BI, matplotlib, ggplot2. - Experience with version control systems (Git) and collaborative development practices. - Strong foundation in statistics, hypothesis testing, and experimental design. - Experience with supervised and unsupervised learning techniques. - Knowledge of data preprocessing, feature engineering, and model validation. - Understanding of A/B testing and causal inference methods. - Experience with cloud platforms and big data technologies such as Spark, Hadoop. What You'll Need to Be Successful (Required Skills) : - Large Language Model (LLM) Experience : At least 5 years of hands-on experience working with pretrained language models (GPT, BERT, T5) including fine-tuning, prompt engineering, and model evaluation techniques. - LLM experience should include Claude, Llama models. - Understanding of RAG techniques is a critical skill. - Generative AI Frameworks : Proficiency with generative AI libraries and frameworks such as Hugging Face Transformers, Lang Chain, OpenAI API, or similar platforms for building and deploying AI applications. - Prompt Engineering and Optimization : Experience designing, testing, and optimizing prompts for various use cases including text generation, summarization, classification, and conversational AI applications. - Vector Databases and Embeddings : Knowledge of vector similarity search, embedding models, and vector databases (Pinecone, we aviate, Chroma) for building retrieval-augmented generation (RAG) systems. - AI Model Evaluation : Experience with evaluation methodologies for generative models including BLEU scores, ROUGE metrics, human evaluation frameworks, and bias detection techniques. - Multi-modal AI Systems : Familiarity with multi-modal generative models combining text, images, and other data types, including experience with vision-language models and cross-modal applications. - AI Safety and Alignment : Understanding of responsible AI practices including content filtering, bias mitigation, hallucination detection, and techniques for ensuring AI outputs align with business requirements and ethical guidelines. Preferred Skills : - At least 1 year of experience working with healthcare data or in healthcare IT environments. - Familiarity with electronic health record (EHR) systems and healthcare workflows. - Understanding of healthcare data privacy regulations (HIPAA, HITECH). - Knowledge of clinical data standards and interoperability frameworks. - Knowledge of MLOps practices and model deployment pipelines. - Familiarity with natural language processing for clinical text analysis. - Experience with time series analysis for patient monitoring data.