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

Position Overview

Responsible for overseeing data science projects, managing and mentoring a team, and aligning data initiatives with business goals. You will lead the development and implementation of data models, collaborate with cross-functional teams, and stay updated on industry trends. The role involves ensuring ethical data use, communicating complex technical concepts to non-technical stakeholders, and leading initiatives on model governance and model ops to meet regulatory and security requirements. This position requires technical expertise, strategic thinking, and leadership to drive data-driven decision-making, and it pioneers generative AI healthcare solutions aimed at revolutionizing healthcare operations and enhancing member experience.

Key Responsibilities

• Research and Development:Stay current with the latest advancements in AI and machine learning and apply these insights to improve existing models and develop new methodologies.
• AI Model Deployment, Monitoring & Model Governance:Deploy AI models into production environments, monitor their performance, and adjust as necessary to maintain accuracy, effectiveness, and regulatory compliance.
• Innovation Projects:Lead pilot projects to test and implement new AI technologies within the organization.
• Data Analysis and Interpretation:Extract meaningful insights from complex datasets, identify patterns, and interpret data to inform strategic decision-making.
• Machine Learning Model Development:Design, develop, and train machine learning models using a variety of algorithms and techniques including supervised, unsupervised, deep learning, and reinforcement learning.
• Agentic Workflows Implementation:Develop and implement AI-driven agentic workflows for autonomous task execution and enhanced operational efficiency.
• RAG Pattern Utilization:Employ retrieval-augmented generation techniques to improve language model performance by effectively utilizing external knowledge.
• Model Fine-Tuning:Fine-tune pre-trained models to adapt them to specific tasks or datasets, ensuring optimal performance and relevance.
• Data Cleaning and Preprocessing:Prepare data by performing cleaning, handling missing values, and removing outliers to ensure high-quality inputs for modeling.
• Collaboration:Work closely with cross-functional teams including software engineers, product managers, and business analysts to integrate AI solutions into existing systems.
• Documentation and Reporting:Create comprehensive documentation of models, methodologies, and results, and communicate findings clearly to non-technical stakeholders.
• Mentor and guide junior data scientists.
• Partner with business and technology teams to build ML models that improve key business objectives such as Star ratings and reducing care gaps.
• Present complex analytical information clearly and concisely to diverse audiences.
• Perform other duties as business requirements evolve, including identifying opportunities for data-driven solutions and technology-enabled processes.
• Utilize a broad range of tools and techniques to extract insights from current industry or sector trends.

Required Qualifications

• Required Education: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 suitable experience in other industries will be considered).
• Knowledge of big data technologies (e.g., Hadoop, Spark) and familiarity with relational database and SDLC concepts.
• Demonstrated critical thinking and the ability to bring order to unstructured problems.
• Technical Proficiency:Strong programming skills in Python and R and experience with machine learning frameworks such as TensorFlow, Keras, or PyTorch.
• Statistical Analysis:Excellent understanding of statistical methods and machine learning algorithms including k-NN, Naive Bayes, SVM, and neural networks.
• Experience with Agentic Workflows:Familiarity with designing and implementing AI agent-driven workflows.
• RAG Techniques:Knowledge of retrieval-augmented generation techniques and their application to enhance AI model outputs.
• Model Fine-Tuning Expertise:Proven experience in fine-tuning models for specific tasks to meet performance metrics.
• Data Visualization:Proficiency in tools such as Tableau or Power BI to effectively present complex data insights.
• Database Management:Experience with SQL and NoSQL databases, data warehousing, and ETL processes.
• Problem-Solving Skills:Strong analytical abilities focused on developing innovative solutions to complex challenges.

Preferred Qualifications

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

Benefits & Perks

• Compensation:Pay Range of $117,731 - $275,491/ANNUAL.Actual compensation may vary based on geographic location, work experience, education and/or skill level.
• Competitive Benefits:Molina Healthcare offers a competitive benefits and compensation package.
• Equal Opportunity Employer:Molina Healthcare is an Equal Opportunity Employer (M/F/D/V).

To all current Molina employees: If you are interested in applying for this position, please apply through the intranet job listing.