Role Description We are seeking a Statistician to join our Data Analytics team. In this role, the Statistician will provide statistical and analytical support for healthcare data analysis projects using a variety of statistical methods and analytical tools. Working under the guidance of senior analytical staff, the Statistician will develop, analyze, and interpret complex datasets to support program integrity, healthcare operations, and business decision-making. This position works both independently and collaboratively with data analysts, statisticians, and project leadership to produce high-quality deliverables for clients. Responsibilities - Perform data extraction, cleaning, validation, transformation, and maintenance across multiple data sources. - Conduct statistical analyses and quantitative data mining to identify trends, patterns, anomalies, and other meaningful insights. - Develop reports, dashboards, summaries, and visualizations to communicate analytical findings. - Compile, validate, interpret, and present data to support operational and business objectives. - Perform statistical programming and data analysis using analytical software and programming languages. - Design and execute database queries to retrieve and analyze data from large datasets. - Prepare clear, concise, and accurate reports, memoranda, data files, and presentations for internal and external stakeholders. - Communicate analytical methods, assumptions, and results to both technical and non-technical audiences. - Support internal quality reviews, audits, and data validation activities. - Participate in team projects, methodology discussions, and continuous process improvement initiatives. - Stay current on statistical methods, healthcare industry trends, data analytics technologies, and applicable regulations. - Perform ad hoc analyses and other duties as assigned. - Maintain compliance with all applicable privacy, security, and confidentiality requirements. - Adhere to IntegrityM policies and client requirements governing the protection of sensitive information. Qualifications - Bachelor's degree in Statistics, Biostatistics, Mathematics, Computer Science, Data Science, or a related quantitative field. - Minimum of two years of experience using statistical programming languages (e.g., SAS, Python, R, or SQL). - Preferred experience with statistical methodologies and relational databases. - Minimum of three years of experience analyzing healthcare, health insurance, or government healthcare program data. - Preferred experience working with healthcare claims, clinical, financial, or administrative datasets. - Advanced knowledge of statistical analysis, quantitative methods, and analytical problem solving. - Proficiency with Python, Databricks, SAS, SQL, Excel, Word, PowerPoint, and other analytical tools. - Experience developing queries, analyzing large datasets, and interpreting complex data. - Strong written and verbal communication skills with the ability to explain technical concepts to non-technical audiences. - Strong organizational, analytical, and problem-solving skills. - Ability to work independently while collaborating effectively within a multidisciplinary team. - Ability to manage multiple priorities and meet established deadlines. - Passion for supporting healthcare program integrity and IntegrityM's mission, vision, values, and operating principles. Benefits - Vacation - Sick leave - Paid holidays - Health insurance - Dental insurance - Vision insurance - Short- and long-term disability - Life insurance - Employee assistance plan - 401(K) retirement plan - Educational benefits

Role Description Your future role at a glance - Location: Remote with about 5% travel - Department: Workforce Intelligence and Insights - Schedule: Day shift | Full-time - Salary range: $96,208.99 - $134,109.89 per year How you'll make an impact in this role: - Use R/Python and SQL to develop, implement, and monitor production-ready data science and machine learning pipelines for predictive modeling. - Navigate complex business and technical scope, stakeholder needs, and practical implications to discern data science opportunities. - Ability to perform exploratory data analysis to identify relevant statistical and machine learning techniques for business insight. - Serves as a technical consultant and translates highly technical information to numerous audiences, including executives, stakeholders, and less-experienced associates. - Design, develop, and monitor solutions leveraging Large Language Models (LLMs) to solve real-world business problems. Qualifications - High School diploma equivalency with 2 years of cumulative experience OR Associate's degree/Bachelor's degree OR 4 years of applicable cumulative job specific experience required. Requirements - Experience with cloud data science platforms such as GCP, Microsoft Azure Machine Learning, or Redshift Sage. - Strong understanding of leveraging HR data to address business challenges, such as pipelining data from survey results or ingesting and structuring Oracle Cloud datasets. Benefits - Paid time off (PTO) - Various health insurance options & wellness plans - Retirement benefits including employer match plans - Long-term & short-term disability - Employee assistance programs (EAP) - Parental leave & adoption assistance - Tuition reimbursement - Ways to give back to your community

• Break down multi-domain business problems with a strong focus on return on investment and impact metrics, and think through the appropriate technical methods from POC to production • Develop solutions and extract insight from data using data science and classical machine learning methods and generative AI (GenAI) • Take ownership of developing, implementing, and automating robust data science and ML models and pipelines, including feature generation, modeling, evaluation, retraining and deployment • Translate sophisticated analytical findings and model outcomes into clear, actionable insights for stakeholders, demonstrably driving value and improvements in key business metrics • Collaborate with cross-functional teams to understand requirements and deliver innovative Data Science/ML/AI solutions • Conduct research on the latest Data Science/ML/AI developments and apply them to improve our systems • Document processes, code, and findings for future reference and knowledge sharing

• Explore data sources and develop new PropertyTech and InsurTech models using data science, including machine learning and deep learning. • Research, design, and implement deep learning algorithms and architectures that extract insights from imagery sources such as aerial imagery and geospatial data. • Lead the development of high-quality datasets for robust model training and evaluation. • Collaborate closely with cross-functional teams to understand requirements and translate product, engineering, and business constraints and questions into actionable data science problems. • Coach and provide feedback to members of the Data Science and Machine Learning team, fostering skill development and knowledge sharing.