Independence Blue Cross

Partner with business leaders across clinical, pharmacy, operations, and other business areas to conceptualize and implement data science solutions that integrate into workflows.. Manage the execution of advanced predictive analytics through visualization, data modeling, forecasting, simulation, and data analytics taken from complex, high-volume, and high-dimensional datasets.. Hands-on expertise building, deploying, and managing machine learning models on cloud platforms like Google Cloud (BigQuery, Vertex AI), AWS (SageMaker, Lambda), or Azure (Machine Learning Studio).. Experience with cloud data warehouses like BigQuery, Redshift, or Snowflake. Knowledge of cloud security, access control, and cost optimization best practices.

data science

Independence Blue Cross serves more than 8.5 million people in 25 states and Washington, D.C., including more than 2.5 million in the Philadelphia, PA region, making it the leading health insurance company in southeastern Pennsylvania. Independence as we and shape the future of healthcare. We are looking for committed, empowered learning-oriented people to join our team. Job Summary As Manager Data Science, you will lead and mentor a talented team of data scientists to deliver innovative solutions that transform healthcare. This is a unique opportunity to work cross-functionally and apply your technical and leadership abilities to high-impact initiatives that improve health and healthcare for millions in the Philadelphia, PA region and beyond. In this role, you will collaborate with diverse business units and utilize cloud platforms and Agile methodologies to implement data science initiatives from conception through deployment. You will oversee the development, evaluation, and ethical implementation of machine learning models using cutting-edge techniques like Generative AI. Your solutions will provide actionable insights that directly improve health outcomes, streamline operations, and enhance the member experience. Responsibilities •Lead and manage a team of highly skilled and dedicated data scientists and analysts, providing mentoring, training opportunities, and fostering a collaborative environment. •Partner with business leaders across clinical, pharmacy, operations, and other business areas to conceptualize and implement data science solutions that integrate into workflows. •Manage the full lifecycle of projects utilizing Agile methodologies - from scoping and planning to development, testing, and deployment. •Provide technical oversight on development, training, evaluation, and implementation of machine learning models including neural networks, regression, clustering, and more. •Oversee the fine-tuning, evaluation, and monitoring of generative models to ensure performance, fairness, and alignment with business needs. •Develop strategies for integrating Generative AI into workflows to increase productivity and enhance decision-making. •Implement MLOps and DevOps best practices for CI/CD and production deployment on cloud infrastructures. •Follow guidelines and best practices fair and responsible AI throughout the development process, including rigorous evaluation of model fairness and performance. •Manage external collaborations with academic institutions and contribute to publications. •Communicate project status, solutions, results and data insights to key stakeholders and leadership. •Present meaningful data insights and predictions to executive and management teams, assist in strategy development, and guide the expansion of business opportunities. •Manage the execution of advanced predictive analytics through visualization, data modeling, forecasting, simulation, and data analytics taken from complex, high-volume, and high-dimensional datasets. Qualifications: Education Master's degree in data science, computer science or related quantitative field, PhD preferred. Experience 5+ years' experience in a data science leadership role, ideally in healthcare Knowledge, Skills, Abilities •Hands-on expertise building, deploying, and managing machine learning models on cloud platforms like Google Cloud (BigQuery, Vertex AI), AWS (SageMaker, Lambda), or Azure (Machine Learning Studio). •Experience with cloud data warehouses like BigQuery, Redshift, or Snowflake •Knowledge of cloud security, access control, and cost optimization best practices. •Excellent analytical and problem-solving skills. Ability to derive strategic insights. •Deep understanding of data governance, quality, and privacy best practices for healthcare data. •Background in Agile methodologies like user stories, sprints, and standups. •Strong project management, cross-functional leadership, and communication abilities. Passion for developing teams and knowledge of coaching best practices.
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