Vets Hired

Manage and streamline data processes, create reports and visualizations, support audits, and provide actionable insights to support strategic decision-making. | Five+ years experience with data visualization tools, ability to create custom queries and reports, strong communication skills, and preferably experience with regulatory compliance programs. | Management Data Analyst, Senior Specialist Summary The Management Data Analyst, Senior Specialist supports strategic decision-making by managing data processes, reporting, and analytics. This role is responsible for preparing reports for both internal stakeholders and external compliance agencies, compiling performance and trend analyses, and supporting audits or data requests. The position also focuses on solving technical database problems, streamlining data processes, and recommending solutions to improve efficiency and accuracy. Responsibilities • Acquire, process, integrate, and clean data from multiple sources to support organizational strategies. • Scope, plan, design, and deliver data analytics activities as part of a forward-looking analytics roadmap. • Ensure data quality and interoperability across datasets to enable reuse. • Streamline data integration processes through scripting and automation of ingestion and transformation. • Promote data literacy within the organization by ensuring stakeholders understand and effectively use analytics tools. • Build partnerships with functional teams to deliver impactful programs through data-driven insights. • Develop and support data structures that can be leveraged across business units. • Create advanced analytics products that provide actionable insights for decision-makers. • Design and build compelling data visualizations to engage audiences and support effective storytelling. • Ensure protection of physical, financial, and cybersecurity assets, maintaining the highest standards of integrity in handling sensitive and confidential data. Minimum Qualifications • Five or more years of experience working with data visualization tools such as Power BI, Tableau, Power Apps, SAS, or similar. Preferred Qualifications • Bachelors degree in Business, Finance, Economics, Engineering, Mathematics, Statistics, or a related discipline. • Ability to create custom database queries and reports. • Experience working with Federal or State regulatory compliance programs (e.g., ISO, NERC/FERC, CPUC). • Experience integrating data from multiple sources and maintaining synchronization on an ongoing basis. • Strong written and verbal communication skills, including experience presenting technical information. Additional Information • Hybrid work mode with a combination of on-site and remote work, subject to business needs. • Candidates must reside and be authorized to work in the state of California. • Consideration will be given to applicants consistent with fair chance hiring practices. • Relocation is not available for this position.

Lead and develop predictive and prescriptive analytics solutions for healthcare clinical, operational, and business challenges, manage projects and mentor teams. | PhD or equivalent experience with 7+ years in ML/AI, statistics, or operations research, proficiency in Python, R, SQL, and experience applying these to healthcare data. | Job Title: Senior Healthcare Data Scientist Machine Learning/AI, Statistics, Operations Research Job Summary This hybrid position involves working both remotely and on-site to facilitate collaboration with interdisciplinary teams. The Senior Healthcare Data Scientist will join the Advanced Data Science group to support strategic priorities by developing and deploying predictive and prescriptive analytics solutions for clinical, operational, and business challenges in healthcare. The role requires experience with Machine Learning/AI, Statistics, and Operations Research, as well as a portfolio demonstrating prior relevant projects. Principal Responsibilities • Lead analytic efforts aligned with organizational priorities and clinical/business problems. • Develop, validate, and deploy predictive (machine learning/deep learning) and prescriptive (optimization/simulation) models. • Work with stakeholders to pilot, test, and validate analytic solutions. • Perform statistical analysis to evaluate pilot outcomes and generate actionable insights. • Develop presentations summarizing analytics results and support organizational strategy. • Build and maintain an analytics portfolio with robust documentation. • Lead cross-functional teams to drive innovation, improve quality of care, reduce costs, and enhance operational efficiency. • Mentor staff on technical aspects and problem-solving in Machine Learning/AI, Statistics, and Operations Research. • Manage project plans, documentation, and stakeholder communications. • Scale successful projects and improve analytics applications based on end-user feedback. • Stay current with state-of-the-art literature in machine learning/AI, statistical modeling, and operations research. • Independently solve complex problems using open-source tools and in-house resources. Qualifications Education & Experience • PhD in applied mathematics, data science, physics, computer science, engineering, statistics, economics, or a related field (or equivalent work experience). • 7+ years of industry experience in Machine Learning/AI, Statistics, or Operations Research. • Proficiency in SQL, Python, and R. • Experience applying computational algorithms, statistical methods, and predictive/prescriptive models to healthcare data. • Experience leading projects and multi-disciplinary teams. • Preferred experience with Natural Language Processing (NLP) and text mining. Knowledge, Skills, and Abilities • Develop machine learning/deep learning algorithms for clinical, operational, or business problems. • Formulate and solve complex mathematical optimization problems using exact and heuristic methods. • Perform exploratory data analysis and advanced statistical analyses (e.g., regression, cluster analysis, ANOVA). • Design and prototype new application functionality. • Work with real-world data, including data cleaning, transformation, and imputation. • Communicate findings clearly through written, oral, and graphical presentations. • Strong knowledge of databases, data structures, and enterprise transaction systems. • Ability to work independently and collaboratively on software and web application development. • Manage projects and cross-functional teams in a fast-paced environment. • Identify data anomalies, debug software, and implement process improvements with attention to detail.