• Create actionable and pragmatic data science models with minimal supervision. • Understands business needs and identifies potential use cases in more than one business unit. • Work with external partners to develop a minimal viable product to meet those needs while resolving any issues that may arise. • Consistently collaborates with fellow data scientists and frequently interacts with business partners, project managers, cross-functional teams, key stakeholders, and other domains to build analytics capabilities and drive business value. • Continuously work to be updated on the latest developments in machine learning and the healthcare industry. • Work with key stakeholders both within R&D and Operations, along with product management to assess the potential value and risks associated with business problems that have the potential to be solved using machine learning and AI techniques. • Develop an exploratory data analysis approach to verify the initial hypothesis associated with potential AI/ML use cases. • Document your approach, thinking and results in standard approaches to allow other data scientists to collaborate with you on this work. • Prepare your final trained model and develop a validation test set for QA. • Work with production operations to deploy your model into production and support them in monitoring model performance. • Participate in other data science teams collaborating with your peers to support their projects. • Participate in knowledge sharing sessions to bring new insights and technologies to the team. • Participate in design sessions to continuously develop and improve the Cotiviti machine learning platform. • Provide End to End value-based solutions, including data pipeline, model creation and application for end user.

• Lead the analysis, design, and implementation of end‑to‑end process improvements across Enterprise Services domains, integrating statistical models and predictive insights to quantify impact and optimize outcomes • Develop and govern standardized process frameworks, documentation, and controls aligned with CORE, ensuring strong data integrity, audit readiness, and SOX compliance • Drive large scale, cross functional transformation initiatives, using techniques such as forecasting, simulation modeling, scenario analysis, and capacity planning • Translate business needs into executable process designs aligned with HRIS, ERP, and digital platforms, ensuring data flows support accurate modeling and analytics • Identify and enable opportunities for automation, digitization, and self‑service, including advanced workforce analytics, decision systems, and workflow telemetry • Establish and monitor KPIs, SLAs, and enterprise metrics, providing statistical analysis and executive decision support tools to ensure benefit realization and operational transparency • Lead change management efforts including stakeholder engagement, communication strategies, and training on data driven decision making and process design • Provide mentorship and functional leadership to process engineers, analysts, and CORE team members, strengthening enterprise analytics and continuous improvement capabilities • Travel ~25% as required

• Wir sind die DataSmart Point Academy, ein spezialisierter Weiterbildungsträger mit Fokus auf digitale Zukunftskompetenzen. • In 6, 8 oder 12 Monaten lernst du alles, was du für deinen Einstieg brauchst – mit anerkanntem IHK-Abschluss und praktischen Skills in Excel, SQL, Power BI und Python. • Tools: Excel, SQL, Power BI – Fokus: Geschäftsprozesse verstehen, Daten analysieren, Entscheidungen optimieren. • KI-Modelle bauen, Prozesse automatisieren, tief in die Technik eintauchen.

• Test, maintain, and enhance our marketing strategies across numerous distribution channels. • Expand and diversify Root’s direct marketing portfolio by shepherding new mid-upper funnel channels from R&D to production. • Rapidly prototype, test, and iterate on novel marketing strategies in the mid and upper funnel. • Design time- and cost-efficient A/B tests that enable rigorous measurement of the incremental profit impact of marketing campaigns. • Deliver clear and prompt communication of research results that drive action to leaders and stakeholders.