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. JobSummary: The Senior 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 Senior Data Scientist will design, deliver, andoptimizepowerful insights and visuals with advanced analytics and AI, including effective use of AI assistants within development tools to accelerate planning, solution design, implementation, and documentation. The Senior Data Scientistis expected topossessexpert business, data, and analyticsexpertiseto handle complex advanced analytics initiatives. TheSenior Data Scientistis self-motivated and able to work under limited supervision from management, can manage multiple complex and significant projects simultaneously, andis responsible formaking connections and integrating work across teams and departments. Working closely with data solutions architects and other leaders, theSenior Data Scientistensures alignment of prioritization of work andappropriate allocationof resources, while applying responsible, secure, and privacy-aware AI-assisted workflows (human-in-the-loop review, traceability, and validation of AI-generated outputs). Thisrolewill lead efforts around process improvement to enhance team effectivenessinleveragingadvanced analytics tools and techniques in our Google Cloud environment.In support of the Data Literacy Program, theSenior Data Scientistwillbe responsible fordeveloping trainingand informationmaterials on newtechniques/tools/reports across the enterprise to ensure rapid and effective adoption ofinsights derived fromadvanced analytics techniques. Responsibilities: Data Exploration: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 tocollect andanalyze large datasetsandidentifypatternsby developingpredictive models,deep learning algorithms, and frameworksusing tools like TensorFlow andPyTorch.Leveragemodel farms and other AI repositories fordevelopmentof innovative data processing pipelines to deliver value to the business. Model Development:Design, build, andvalidatepredictive models to solve business problems.Provide team leadership to ensureprovenance and traceability inMLOpsdevelopment cycles. Data Visualization:Create compelling visualizations to communicate findings and insights to stakeholders. Collaboration:Work closely with business leaders, product managers,data scientists,and engineers to translate business requirements into analytical solutions. AI-Assisted Planning & Design:Use AI assistants to acceleraterequirementsclarification, solution options, and technical design; convert outputs into reviewed artifacts (design docs, user stories, test plans). AI-Assisted Implementation:Use AI coding assistants to draft code/queries/notebooks/pipelines; perform human review for correctness, security, performance, and maintainability; follow IP/licensing and data-use policies. QA Oversight:Define acceptance criteria, test strategy, and validation methods (data checks; model metrics and bias/robustness as applicable); partner with engineering/QA on regression coverage and release readiness. AI-Teaming & Refinement:Iteratively refine solutions using prompt engineering, grounding/source practices, andevaluationrubrics; document prompts, assumptions, and decisions for repeatability. Mentorship:Provideguidance and mentorship toother datascientists,analystsand engineerswithin 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. Evangelism:Evangelize withincompanythe capabilities and opportunities that data science and advanced analytics empower towards corporate goals. Question,validate,and perform quality assurance of the data for integrity and consistency to supportongoing data quality assessment and improvementinitiatives. Understandall applicable data privacyand security laws, rules,regulations, and contractual restrictions, and follow all Surescripts data governance and data usage rights policies and procedures. Documentaccess and userequirements foradvanced analyticsdata/reporting products and support the definition of report template and specifications. Demonstrate ability to communicate complex analytic results in a clear and concise fashion to sponsors/clients at all levels, and to audiences of all sizes. Summarize and synthesize large bodies of work down to the essential elements and convey those results effectively and efficiently, in both written and oral form, to the most senior leaders in client organizations. Effectively communicate with & engage colleagues at all levels of the organization. Effectively delegateresponsibilities to theappropriate peopleand levels. Develop internal and external networks of contacts and havea positive influence on those networks. Play a key role in supporting corporate initiatives andsupportsenior leadership initiatives to realize Surescripts' goals. Qualifications: Basic Requirements: Master'sdegreein Mathematics, Computer Science, Statistics, or other related field;or equivalent experience 5+ yearsof experience indata science,datamanagement and/or applying data analysis and reporting skills in a business @context 5years of experience with largehealthcaretransactional datasets/reporting 5years of experience in healthcare transaction data, including QA,testingand reporting Expertisein programming languages tofacilitateanalysis (e.g.R, Python or MATLAB) Expertisewith SQL /PLSQL, Relational and NoSQL databases, and Structured and Unstructured data Analytical background and research experience with large volumesof personaldata Ability to translate statistical analysis into a written and verbal presentation fornon-data science audience. Experienceinstatistical modeling using healthcare data Experience developing training material and delivering training to user groups of10or more Knowledge of privacy laws and regulations around health data (HIPAA) Demonstratedproficiencyusing AI assistants across planning, design, implementation, and documentation (e.g., IDE/code assistants such as GitHub Copilot or Claude Code; chat-based assistants such as Microsoft Copilot; notebook/workbench assistants), with human review, traceability, and validation of AI-generated outputs. Demonstrated experience providing QA oversight for analytics/ML deliverables (defining acceptance criteria, designing validation approaches, partnering with engineering/QA on test automation and release readiness). Experience with AI-teaming techniques for refining technical solutions (prompt engineering, grounding/citation practices, evaluation rubrics and benchmarking, and documentation of AI-assisted decisions), includingidentifyingand mitigating common failure modes (e.g., hallucinations, data leakage, insecure... For full info follow application link. Equal Employment Opportunity/Affirmative Action Employer - Disabled/Vets
