Principal Data Scientist - Generative AI, Machine Learning, Python, R - Remote

Position Overview

Responsible for overseeing data science projects, managing and mentoring a team, and aligning data initiatives with business goals. Lead the development and implementation of data models, collaborate with cross-functional teams, and stay updated on industry trends. Ensure ethical data use and communicate complex technical concepts to non-technical stakeholders. Lead initiatives on model governance and model ops to align with regulatory and security requirements. This role requires technical expertise, strategic thinking, and leadership to drive data-driven decision-making within the organization and be the pioneer on generative AI healthcare solutions, aimed at revolutionizing healthcare operations as well as enhancing member experience.

Key Responsibilities

• Research and Development: Stay current with the latest advancements in AI and machine learning to improve existing models and develop new methodologies.
• AI Model Deployment, Monitoring & Model Governance: Deploy AI models into production, monitor performance, and adjust to meet accuracy and regulatory requirements.
• Innovation Projects: Lead pilot projects to test and implement new AI technologies within the organization.
• Data Analysis and Interpretation: Extract insights from complex datasets, identify patterns, and inform strategic decision-making.
• Machine Learning Model Development: Design, develop, and train models using supervised, unsupervised, deep learning, and reinforcement learning techniques.
• Agentic Workflows Implementation: Develop workflows that utilize AI agents for autonomous task execution and enhanced operational efficiency.
• RAG Pattern Utilization: Employ retrieval-augmented generation patterns to enhance language model outputs with external knowledge.
• Model Fine-Tuning: Fine-tune pre-trained models to ensure optimal performance and relevance for specific tasks.
• Data Cleaning and Preprocessing: Prepare and clean data by handling missing values and removing outliers.
• Collaboration: Work closely with cross-functional teams including software engineers, product managers, and business analysts.
• Documentation and Reporting: Create comprehensive documentation of models, methodologies, and results for non-technical stakeholders.
• Mentorship: Mentor and coach newer data scientists.
• Business Partnership: Partner with business and technology teams to build ML models that improve star ratings, reduce care gaps, and meet business objectives.
• Presentation: Present complex analytical information clearly to various audiences.
• Project Management: Collaborate with analytics teams to assign and manage analytical project delivery.
• Other Duties: Adapt to changing business requirements by identifying innovative data and technology solutions.
• Industry Insight: Use a broad range of tools to extract insights from current industry or sector trends.

Required Qualifications

• Master's Degree in Computer Science, Data Science, Statistics, or a related field.
• 10+ years' work experience as a data scientist, preferably in a healthcare environment (candidates with relevant experience from other industries will be considered).
• Knowledge of big data technologies (e.g., Hadoop, Spark) and relational database concepts.
• Understanding of SDLC concepts and the ability to bring order to unstructured problems.
• Strong technical proficiency with programming languages such as Python and R, and experience with machine learning frameworks like TensorFlow, Keras, or PyTorch.
• Excellent understanding of statistical methods and machine learning algorithms (e.g., k-NN, Naive Bayes, SVM, and neural networks).
• Familiarity with designing and implementing agentic workflows for autonomous operations.
• Knowledge of retrieval-augmented generation techniques to enhance AI outputs.
• Proven experience in fine-tuning models to meet specific performance metrics.
• Proficiency in data visualization tools (e.g., Tableau, Power BI) to present complex insights.
• Experience with SQL and NoSQL databases, data warehousing, and ETL processes.
• Strong analytical and problem-solving skills.

Preferred Qualifications

• PhD or additional experience.
• Experience with cloud platforms (e.g., Databricks, Snowflake, Azure AI Studio) for AI workflows and model deployment.
• Familiarity with natural language processing (NLP) and computer vision techniques.

Benefits & Perks

• Compensation: Pay Range: $117,731 - $275,491 / ANNUAL (actual compensation may vary based on geographic location, work experience, education and/or skill level).
• Employment Type: Full Time.
• Benefits: Molina Healthcare offers a competitive benefits package.