Data Scientist-Applications (Onsite)

Responsibilities:

• Design, develop, and optimize machine learning models for production environments.
• Build scalable AI systems, including data pipelines, model training, and deployment frameworks.
• Work with deep learning frameworks (TensorFlow, PyTorch) and traditional ML libraries (Scikit-learn, XGBoost).
• Collaborate with cross-functional teams to integrate AI solutions into existing products and services.
• Optimize models for performance, scalability, and efficiency in cloud or on-prem environments.
• Stay up to date with the latest advancements in AI/ML and apply best practices to ongoing projects.
• Conduct experiments, analyze performance, and iterate on models to enhance accuracy and efficiency.
• Mentor junior engineers and contribute to the AI/ML technical strategy.
• Design and develop strategy for 
  • medical language learning through language models
  • medical code and group code (per various specifications) using large language model
  • contract interpretation
  • transforming rules and workflows into decision tree using deep learning ML models
  • risk detection/anomaly detection using deep learning ML model
• Work with Engineering team to lay out training data acquisition strategy
• Lay out the process for ML use case evaluation and planning
• Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval 
• Collaborate with engineers to integrate machine learning models into production systems, ensuring scalability, reliability, and performance
• This role is hybrid and based in Overland Park, KS.

Requirements:

✅ Education & Experience:

• Bachelor’s, Computer Science or AI, Data Science, or a related field.
• 5+ years of experience in AI/ML development, with a strong track record of building and deploying models.

✅ Technical Skills:

• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (MLflow, Kubeflow, Airflow).
• Strong background in data preprocessing, feature engineering, and model optimization.
• Familiarity with deep learning architectures (CNNs, RNNs, Transformers) and NLP techniques.
• Experience with big data technologies (Spark, Hadoop) is a plus.
• Knowledge of DevOps, CI/CD for AI models, and containerization (Docker, Kubernetes) is a plus.

✅ Soft Skills:

• Strong problem-solving and analytical skills.
• Ability to work in a fast-paced, collaborative environment.
• Excellent communication skills to convey complex AI concepts to
• stakeholders.

Preferred Qualifications:

• Master’s Degree
• AWS Cloud Experience