Senior Data Scientist at Enable Data Incorporated | USA | Rezi

Senior Data Scientist at Enable Data Incorporated

Senior Data Scientist

Enable Data Incorporated · USA

1 weeks ago

Senior Data Scientist

Enable Data Incorporated · USA

8 days ago
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About the Role

Seeking a Senior Data Scientist to design, develop, and deploy end-to-end AI/ML solutions for predictive modeling, risk stratification, behavioral analytics, and treatment pathway prediction. This role involves building advanced NLP, LLM, and RAG-based applications, as well as speech and conversational AI capabilities.

Responsibilities

  • 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

  • Predictive Modeling
  • Risk Stratification
  • Behavioral Analytics
  • Treatment Pathway Prediction
  • NLP
  • LLM
  • RAG
  • Prompt Engineering
  • Fine-tuning
  • Clinical AI Guardrails
  • Speech AI
  • Conversational AI
  • ASR
  • Sentiment Analysis
  • Intent Classification
  • Text-to-SQL
  • Decision-support Models
  • A/B Testing
  • Cohort Analysis
  • Explainability (SHAP/LIME)
  • Drift Monitoring
  • HIPAA Compliance
  • Feature Stores
  • MLflow
  • MLOps
  • CI/CD Pipelines
  • Real-time Inference
  • Batch Inference
  • Python
  • Pandas
  • NumPy
  • Scikit-learn
  • PyTorch
  • TensorFlow
  • XGBoost
  • LightGBM
  • Survival Analysis
  • Time-series Forecasting
  • Deep Learning
  • Transformer Models (BERT/GPT)
  • Hugging Face
  • LangChain
  • Vector Databases
  • LLM Fine-tuning
  • LLM Evaluation
  • Speech AI
  • Databricks (Delta Lake, MLflow, Spark)
  • AWS (S3, SageMaker, Bedrock, Redshift, Athena)
  • SQL
  • Docker
  • Kubernetes

Work Type

  • Full-Time
  • FTE

Experience Level

  • Senior
  • 7+ years