Immediate Full-Time Position for Senior Data Scientist (This will be FTE only)
Design, develop, and deploy end-to-end AI/ML solutions for predictive modeling, risk stratification, behavioral analytics, and treatment pathway prediction.
Build advanced NLP, LLM, and RAG-based applications, including prompt engineering, fine-tuning, and clinical AI guardrails for extracting insights from unstructured data.
Develop speech AI and conversational AI capabilities using ASR, sentiment analysis, intent classification, Text-to-SQL, and decision-support models to improve care outcomes.
Measure model performance through A/B testing, cohort analysis, explainability (SHAP/LIME), drift monitoring, and HIPAA-compliant governance.
Collaborate with Data Engineering to implement feature stores, MLflow, MLOps, CI/CD pipelines, and scalable real-time/batch inference solutions.
Mentor junior data scientists, evaluate emerging AI technologies, and drive the AI roadmap by translating advanced models into actionable healthcare solutions.
Requirements
7+ years of hands-on data science experience building and deploying predictive analytics, NLP, and Generative AI solutions in production, preferably within healthcare or other regulated industries.
Proven expertise across the entire machine learning lifecycle, including feature engineering, model development, deployment, monitoring, and optimization.
Advanced Python skills with pandas, NumPy, scikit-learn, PyTorch, and TensorFlow, along with classical ML techniques such as XGBoost, LightGBM, survival analysis, time-series forecasting, and deep learning.
Strong experience with LLMs, RAG architectures, transformer models (BERT/GPT), Hugging Face, LangChain, vector databases, and LLM fine-tuning and evaluation.
Hands-on expertise with NLP, speech AI, Databricks (Delta Lake, MLflow, Spark), AWS (S3, SageMaker, Bedrock, Redshift, Athena), SQL, Docker, Kubernetes, and MLOps practices.
Demonstrated leadership through mentoring, cross-functional collaboration, and the ability to communicate complex AI/ML insights to technical and business stakeholders while driving innovation and best practices.
Skills Required
- 7+ years hands-on data science experience building and deploying predictive analytics, NLP, and Generative AI solutions in production (preferably healthcare or regulated industries)
- Proven expertise across the entire machine learning lifecycle: feature engineering, model development, deployment, monitoring, and optimization
- Advanced Python skills with pandas, NumPy, scikit-learn, PyTorch, and TensorFlow
- Experience with classical ML techniques: XGBoost, LightGBM, survival analysis, time-series forecasting, and deep learning
- Strong experience with LLMs, RAG architectures, transformer models (BERT/GPT), Hugging Face, LangChain, vector databases, and LLM fine-tuning/evaluation
- Hands-on expertise with NLP, speech AI (ASR, sentiment, intent), Text-to-SQL, and conversational AI/decision-support models
- Experience with Databricks (Delta Lake, MLflow, Spark), AWS (S3, SageMaker, Bedrock, Redshift, Athena), SQL, Docker, Kubernetes, and MLOps practices
- Experience implementing HIPAA-compliant governance and privacy controls for healthcare data and models
- Demonstrated leadership: mentoring junior data scientists and communicating complex AI/ML insights to technical and business stakeholders
What We Do
Enable Data specializes in advanced data, application and cloud solutions working on cutting-edge projects driving innovation and transformation for our customers. We empower our customers to leverage modern solutions to deliver increased value across their business ecosystem. We help clients by providing consulting, managed project and staff augmentation services working with clients across various industries including healthcare, financial, media, insurance, and manufacturing.
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