Sr Data Scientist - ML/AI/Databricks - Remote

$116,758 - $227,679/Yr

Molina Healthcare

Full-time - Mid Level

Remote

Insurance Carriers and Related Activities

About the position

The Sr Data Scientist role at Molina Healthcare focuses on leveraging machine learning and AI technologies to enhance healthcare products and services. The position involves performing data analysis, developing and deploying advanced machine learning models, and collaborating with cross-functional teams to drive business decisions through data-driven insights. The role requires a strong background in data science, statistical analysis, and experience with big data technologies, with a particular emphasis on improving healthcare outcomes.

Responsibilities

• Extract meaningful insights from complex datasets, identify patterns, and interpret data to inform strategic decision-making.
• Design, develop, and train machine learning models using various algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
• Develop and implement agentic workflows that utilize AI agents for autonomous task execution, enhancing operational efficiency and decision-making capabilities.
• Employ retrieval-augmented generation patterns to improve the performance of language models, ensuring they can access and utilize external knowledge effectively.
• Fine-tune pre-trained models to adapt them to specific tasks or datasets, ensuring optimal performance and relevance in various applications.
• Prepare data for analysis by performing data cleaning, handling missing values, and removing outliers to ensure high-quality inputs for modeling.
• Deploy AI models into production environments, monitor their performance, and adjust as necessary to maintain accuracy and effectiveness.
• Work closely with cross-functional teams, including software engineers, product managers, and business analysts, to integrate AI solutions into existing systems and processes.
• Stay current with the latest advancements in AI and machine learning and apply these insights to improve existing models and develop new methodologies.
• Create comprehensive documentation of models, methodologies, and results; communicate findings clearly to non-technical stakeholders.
• Mentor, coach, and provide guidance to newer data scientists.
• Partner closely with business and other technology teams to build ML models that help improve Star ratings, reduce care gaps, and meet other business objectives.
• Present complex analytical information to all levels of audiences in a clear and concise manner.
• Collaborate with the analytics team, assigning and managing delivery of analytical projects as appropriate.
• Perform other duties as business requirements change, looking for data solutions and technology-enabled solution opportunities.

Requirements

• Master's Degree in Computer Science, Data Science, Statistics, or a related field.
• 6+ years' work experience as a data scientist, preferably in a healthcare environment.
• Knowledge of big data technologies (e.g., Hadoop, Spark).
• Familiarity with relational database concepts and SDLC concepts.
• Strong programming skills in 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, including k-NN, Naive Bayes, SVM, and neural networks.
• Familiarity with designing and implementing agentic workflows that leverage AI agents for autonomous operations.
• Knowledge of retrieval-augmented generation techniques and their application in enhancing AI model outputs.
• Proven experience in fine-tuning models for specific tasks, ensuring they meet the required performance metrics.
• Proficiency in data visualization tools (e.g., Tableau, Power BI) to present complex data insights effectively.
• Experience with SQL and NoSQL databases, data warehousing, and ETL processes.
• Strong analytical and problem-solving abilities.

Nice-to-haves

• PhD or additional experience in a related field.
• Experience with cloud platforms (e.g., Databricks, Snowflake, Azure AI Studio) for working with AI workflows and deploying models.
• Familiarity with natural language processing (NLP) and computer vision techniques.

Benefits

• Competitive benefits and compensation package.