• Develops actionable insights to help identify, understand, and resolve moderately complex business problems • Leverages big data and innovative problem-solving techniques to forecast future trends and outcomes based on past data patterns • Works individually, as well as with higher-level data scientists, designing experiments to solve problems with code and building predictive models and machine learning algorithms tailored to solve intricate business challenges • Develops an in-depth understanding of the business's needs and objectives, enabling the identification and formulation of pertinent questions that can be effectively addressed through data analysis • Applies deep learning algorithms and models for tasks such as image recognition, natural language processing, and other complex patterns • Applies highly developed knowledge when applying advanced statistical methods to analyze complex datasets, uncovering nuanced insights and relationships • Acts as a top-level specialist, optimizing machine learning models for efficiency, scalability, and improved performance in real-world applications • Develops strategy for expertly selecting and engineering features to enhance model interpretability, accuracy, and generalization • Designs and conducts A/B tests and experimentation to evaluate the impact of changes and interventions • Leads cross-functional collaboration efforts, working closely with diverse teams to integrate data science solutions into business operations • Develops algorithms that can scale to handle large datasets and complex computations, ensuring efficiency in processing • Implements systems to deploy machine learning models into production environments, enabling their integration into operational systems • Develops automated data pipelines for efficient data collection, processing, and integration, streamlining the end-to-end data science workflow

ABOUT THIS POSITION The Data Science focus specializes in extracting insights and solving complex problems using advanced statistical analysis, machine learning, and predictive modeling. Collects, cleans and analyses large datasets to uncover patterns and make data-driven decisions. Responsibilities include developing algorithms, building predictive models, and communicating findings through data visualization. This role often requires a PhD in a statistics field. This job family is in the professional level category and works independently with flexibility and authority over daily work priorities. Incumbents in this job level category may provide work direction to other employees but would not typically have the authority to discipline or reward other employees. There are different levels available that provide clarity on contribution expectations based on knowledge, application, problem solving, and collaboration. WHAT YOU'LL DO * Clean, transform, and analyze large, complex datasets to identify trends, patterns, and insights relevant to business objectives. * Assist in the development and implementation of statistical models, machine learning algorithms, and predictive analytics solutions. * Prepare and present findings and recommendations to technical and non-technical stakeholders in a clear and concise manner. * Collaborate with engineering, product, and business teams to understand data needs and translate them into actionable data science initiatives. * Develop and maintain data visualizations and dashboards to monitor key performance indicators and track model performance. * Participate in code reviews and contribute to maintaining high-quality, well-documented data science code. * Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence. * Support data governance and data quality initiatives. WHAT YOU'LL NEED * Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field. Master's degree preferred. * 1-3 years of professional experience in a data science, data analysis, or analytical role. * Proficiency in Python or R for data analysis and statistical modeling. * Strong understanding of statistical concepts, hypothesis testing, and experimental design. * Experience with SQL for data extraction and manipulation. * Familiarity with machine learning algorithms (e.g., regression, classification, clustering) and their applications. * Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn). * Excellent problem-solving skills and a strong analytical mindset. * Ability to communicate complex data findings effectively to diverse audiences. * Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark) is a plus. ABOUT WAYSTAR Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle. Waystar’s healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful, optimistic & fun. Waystar products have won multiple Best in KLAS® or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book™ surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.com or follow @Waystar on Twitter. WAYSTAR PERKS - Competitive total rewards (base salary + bonus, if applicable) - Customizable benefits package (3 medical plans with Health Saving Account company match) - We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays - Paid parental leave (including maternity + paternity leave) - Education assistance opportunities and free LinkedIn Learning access - Free mental health and family planning programs, including adoption assistance and fertility support - 401(K) program with company match - Pet insurance - Employee resource groups Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

• Definir visão, arquitetura e estratégia técnica para IA generativa; • Desenvolver soluções com agentes autônomos, copilotos inteligentes e assistentes personalizados; • Atuar como referência técnica para o time de ciência de dados, apoiando no desenvolvimento técnico e adoção de boas práticas; • Propor e implementar padrões de engenharia de software e ciência de dados, como versionamento, reprodutibilidade e documentação; • Colaborar com times de engenharia, produto e dados para garantir integrações eficientes e uso sustentável da infraestrutura de dados.

• Desenvolver soluções técnicas que atendam os requisitos de negócio, buscando a criação de aplicações escaláveis e performáticas; • Desenvolver sistemas batch e APIs Rest em linguagem Python, baseado na documentação fornecida, criando aplicação que atendam às exigências do usuário; • Realizar manutenção em portais web; • Identificar, corrigir incidentes e realizar manutenção em sistemas, de acordo com a descrição do problema e a análise de logs; • Elaboração de documentação técnica da solução implementada; • Elaboração de testes unitários; • Capacidade de interação com área de negócios com objetivo de elucidar requisitos de negócios, homologar sistemas desenvolvidos e contribuir com informações técnicas em reuniões de alinhamento da demanda; • Desejável ter atuado com metodologias ágeis; • Desenvolver e avaliar soluções baseados em IA generativa (LLMs) aplicadas a problemas reais de negócio, como recomendação de produtos, análise de documentos, chatbot e estratégias de cobrança; • Conduzir experimentos para otimização de modelos, incluindo prompt engineering, fine-tunning e técnicas de RAG (Retrieval -Augmented Generation); • Definir e implementar métricas de avaliação para modelos generativos (ex: qualidade, factualidade, consistência e viés); • Realizar análises estatísticas robustas para validação de resultados, incluindo testes de hipótese, intervalos de confiança e simulações; • Identificar riscos e propor soluções para mitigação de alucinações, vieses e problemas de confiabilidade.