Surescripts serves the nation through simpler, trusted health intelligence sharing, in order to increase patient safety, lower costs and ensure quality care. We deliver insights at critical points of care for better decisions - from streamlining prior authorizations to delivering comprehensive medication histories to facilitating messages between providers. Job Summary: The Principal Data Scientist will play a pivotal role in developing and implementing data-driven solutions across various business functions, collaborating with cross-functional teams to analyze complex data sets, derive actionable insights, and drive strategic decision-making. The incumbent will lead data science efforts on cross-functional teams to resolve complex problems where analysis of situations or data requires an in-depth evaluation of participant interfaces to Surescripts data platforms and advanced analytics techniques. The Principal Data Scientist will drive project direction to design, deliver, and optimize powerful insights with a focus on, but not limited to, advanced analytics and AI. The incumbent will demonstrate leadership is selection of appropriate machine learning and AI techniques that are to be applied to business opportunities. The Principal Data Scientist is expected to possess sufficient business, data, and analytics expertise to handle complex advanced analytics initiatives. The incumbent will manage multiple complex and significant projects simultaneously. Working closely with leaders within Data and Analytics, and Network Technology and Operations, the incumbent ensures alignment of prioritization of work and appropriate allocation of resources. This role will advise on staffing of cross-functional teams for projects, balancing data scientist resources across internal and external facing company priorities. In support of the Data Literacy Program, the Principal Data Scientist will be responsible for developing training materials on new techniques/tools/reports across the enterprise to ensure rapid and effective adoption of insights derived from advanced analytics techniques. Responsibilities: Data Exploration:Prioritize dataset selection for business use cases and corporate initiatives. Explore and preprocess data from various sources, measuring and ensuring data quality and integrity. Enrich data with external, auxiliary, or commercial data sets to enhance suitability for monetization or AI/ML. Advanced Analytics:Apply statistical and machine learning techniques to collect and analyze large datasets and identify patterns by developing predictive models, deep learning algorithms, and frameworks using tools like TensorFlow and PyTorch. Leverage model farms and other AI repositories for development of innovative data processing pipelines to deliver value to the business. Lead exploratory evaluation and AI/ML research efforts for both emerging AI/ML capabilities as well as emerging data capabilities. Model Development:Design, build, and validate predictive models to solve business problems. Provide team leadership to ensure provenance and traceability in MLOps development cycles. Investigate state-of-the-art and emerging AI/ML technologies for suitability to company use cases and process improvements. Data Visualization:Drive conceptualization of visualization dashboards and other data visualization to be implemented by data science teams to optimally convey data value and insights and enhance decision making for stakeholders. Collaboration:Lead collaboration with business leaders, product managers, data scientists, and engineers to translate business requirements into analytical solutions. Communicate capabilities and limitations of data science, AI, and machine learning to stakeholders to assist with project expectations, management, scope, and staffing. Mentorship:Collaborate to develop overall mentorship program for data science and advanced analytics. Provide guidance and mentorship to other data scientists, analysts and engineers within the team. Serves as a mentor/role model, imparting analytic knowledge, experience, and skills to other staff at all levels, either individually or as a member of project teams. Continuous Learning:Stay abreast of industry trends, emerging technologies, and best practices in data science. Set strategic direction for data scientists' professional development. Evangelism: Evangelize within company the capabilities and opportunities that data science and advanced analytics empower towards corporate goals. Disseminate key information from industry, conferences, and academic venues including the latest trends and capabilities of AI/ML to enhance data systems and solutions. Draft and disseminate company-wide and cross-functional communications including communication for new AI and Advanced Analytics tooling, roadmaps, events, and training. Provide strategic oversight and leadership of quality assurance of the data for integrity and consistency to support ongoing data quality assessment and improvement initiatives. Understand all applicable data privacy and security laws, rules, regulations, and contractual restrictions, and follow all Surescripts data governance and data usage rights policies and procedures. Expertly communicate complex analytic results in a clear and concise fashion to sponsors/clients at all levels, and to audiences of all sizes and all levels. Effectively delegate responsibilities to the appropriate people and levels. Develop internal and external networks of contacts and have a positive influence on those networks. Play a key role in supporting corporate initiatives and support senior leadership initiatives to realize Surescripts' goals. Qualifications: Basic Requirements: Master's degree in Mathematics, Computer Science, Statistics, or other related field; or equivalent experience 8+ years of experience in data science, data management and/or applying data analysis and reporting skills in a business @context 8+ years of experience with large transactional healthcare datasets/reporting 8+ years of experience in healthcare transaction data, including QA, testing and reporting Expertise in programming languages to facilitate analysis (e.g. R, Python or MATLAB) Expertise with SQL /PLSQL, Relational and NoSQL databases, and Structured and Unstructured data Extensive analytics and research experience with large volumes of personal data Ability to translate statistical analysis into a written and verbal presentation for non-data science audience. Extensive Health IT industry knowledge Statistical modeling using healthcare data. Experience and developing training material and delivering training to user groups of 10 or more Expertise in statistical analysis and rigor, statistical software (e.g., R, SPSS, or SAS) Experience with large language models or natural language processing. Project management experience Knowledge of privacy laws and regulations around health data (HIPAA) Experience developing in data science workbench environments (JupyterLab or others) and migrating data science projects to production systems (MLOps) Knowledge of data governance, privacy practices, compliance Preferred Qualifications: PhD degree in a quantitative field (e.g., Data Science, Statistics) or MBA Google Cloud environment expertise Experience with MLOps frameworks such as GCP Vertex AI, DataBricks, or Snowflake Team leadership and mentoring experience Surescripts embraces flexibility through its Flexible Hybrid Work model for most positions. This model allows employees to work virtually while still utilizing our offices as collaboration centers. With alignment and agreement from your leadership, you can come and go from the office as... For full info follow application link. Equal Employment Opportunity/Affirmative Action Employer - Disabled/Vets
