Senior Data Scientist

Job not on LinkedIn

🔥 1 hour ago

❄️ Minnesota – Remote

❄️ Minnesota – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Enable Data

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

Enable Data is a company that offers modern IT solutions to empower its customers by leveraging innovative data analytics and cloud platforms to drive increased value across their business ecosystem. They specialize in the implementation of large-scale SAS applications, distributed rules engines for processing health-related data, and managing data ingest frameworks. Enable Data serves industries requiring advanced data analytics and IT solutions, with a particular focus on healthcare quality and big data management.

📋 Description

• 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.