Role Description Leads advanced analytics initiatives that transform complex data into strategic insights and measurable business impact. Oversees the design and execution of predictive modeling, machine learning, and statistical studies that forecast outcomes, inform decisions, and drive operational excellence. Applies deep technical expertise in tools such as SAS, SQL, R, Python, and Tableau to identify trends, variances, and opportunities for improvement, ensuring analyses are clear, actionable, and aligned with organizational priorities. Partners with senior leadership and research teams to uphold scientific rigor in study design, data validity, and methodological integrity, establishing scalable analytic practices that strengthen quality, efficiency, and innovation across the enterprise. Essential Functions - Leads the design and implementation of advanced data analysis strategies, including statistically sound sampling methodologies, predictive modeling, and trend analysis to identify opportunities, variances, and outliers that drive quality improvement and focused investigations. - Develops and applies epidemiologically sound indicators and benchmarks to assess performance and quality of care, ensuring analyses align with established standards and comparative frameworks. - Mentors junior data analysts and scientists in advanced methodologies, coding practices, and statistical interpretation, fostering technical growth and methodological rigor across the team. - Designs and implements high-performance algorithms and machine learning models within distributed computing environments, ensuring scalability, efficiency, and scientific accuracy. - Drives the development of innovative data science solutions and formulates strategic data initiatives that align with organizational objectives and competitive priorities. - Applies deep domain expertise and advanced modeling techniques to integrate complex data from diverse sources, producing actionable insights and solutions for high-impact business and healthcare challenges. - Leads research and innovation initiatives within the data science community, contributing to open-source projects, developing white papers, and promoting thought leadership through knowledge sharing and collaboration. - Develops and oversees the creation of technical reports, analytic studies, and quality improvement publications, ensuring accuracy, clarity, and defensibility of methodologies and results. - Designs and evaluates intervention strategies and re-measurement methodologies to assess the impact of quality improvement initiatives, translating data findings into practical recommendations. - Collaborates with cross-functional leaders to communicate complex data science results in a clear, actionable manner, aligning analytical outcomes with strategic decision-making and long-term organizational goals. Qualifications - Bachelor's Degree required; Master's Degree in Statistics preferred. Requirements - 8 - 11 years required; 12 - 14 years preferred. Benefits - Qlarant is an Equal Opportunity Employer of Minorities, Females, Protected Veterans, and Individuals with Disabilities. - Qlarant is a drug-free workplace. All offers of employment are contingent upon successful completion of pre-employment background and drug screens.

• Desenvolver, treinar e implantar modelos de Machine Learning e IA Generativa. • Trabalhar com LLMs e arquiteturas RAG (Retrieval-Augmented Generation). • Avaliar e otimizar soluções considerando custo, latência e qualidade das respostas. • Construir pipelines de ingestão e processamento de dados textuais utilizando bancos vetoriais. • Desenvolver APIs e aplicações de IA com LangChain, LangGraph, OpenAI e AWS Bedrock. • Desenvolver soluções de Visão Computacional para classificação de imagens, detecção de objetos e segmentação semântica. • Criar e sustentar pipelines de dados, modelos e aplicações de IA em produção. • Atuar com serviços AWS e Azure para desenvolvimento de soluções escaláveis. • Garantir qualidade, segurança, performance e governança das soluções. • Apoiar Product Owners e stakeholders na definição técnica das iniciativas. • Participar de cerimônias ágeis e colaborar com times multidisciplinares.

• Translate business needs into data analysis and actionable insights to optimize product performance and user experience for both existing and new products. • Work closely with product managers, engineers, and other cross-functional stakeholders to identify critical product questions and provide data-driven solutions. • Develop and maintain a scalable, reliable, and accurate analytics infrastructure to support product decisions. • Establish and maintain best practices for data collection, analysis, and reporting. • Deliver actionable insights and recommendations focused on landing tangible product impact. • Help foster a culture of data-driven decision-making and continuous improvement within the product teams. • Ensure the integrity and accuracy of the data used for analysis and reporting. • While the primary focus is on existing products, support 0 to 1 product launches by identifying key metrics and analyzing early-stage product data when applicable.

Role Description The Senior Data Scientist is a highly skilled individual contributor responsible for leading advanced statistical and machine learning initiatives to solve complex business challenges using large-scale healthcare data. This role owns the end-to-end analytical process, including designing modeling approaches, developing and validating models, and translating business questions into technical solutions. The Senior Data Scientist partners closely with data engineering and cross-functional teams to operationalize models and ensure their performance and scalability in production environments. Success in this role requires strong technical judgment, the ability to communicate insights to diverse stakeholders, and a commitment to analytical rigor and reproducibility. The Senior Data Scientist is a full-time, remote, exempt position and reports to the Sr. Director, Data Science & Advanced Analytics. Qualifications - 4–7 years of experience building statistical or machine learning models using large datasets - Advanced degree in Computer Science, Engineering or relevant field; PhD in Data Science or another quantitative field is preferred. Requirements - Lead the development, validation, and refinement of advanced statistical and machine learning models for complex business problems. - Serve as the primary analytical owner for assigned initiatives, with accountability for model quality, analytical rigor, and timely delivery of results. - Design analytical approaches and modeling strategies, translating business questions into well-defined technical solutions. - Perform advanced feature engineering, exploratory data analysis, and model evaluation using large, complex healthcare datasets. - Partner with Data Engineering and Information Systems teams to translate modeling approaches into production-ready solutions, while engineering teams own deployment and operations. - Support production models through performance analysis, monitoring, and retraining activities. - Design and execute experiments to test hypotheses and measure the impact of analytical solutions. - Evaluate new data sources and assess their suitability, quality, and limitations for modeling and analysis. - Communicate analytical findings, model behavior, and key assumptions to stakeholders with varying levels of technical expertise. - Document analytical methods, decisions, and results to support reproducibility and knowledge sharing. - Provide peer-level technical guidance and code review to Data Scientists and Analysts, supporting their development without formal leadership responsibility. - Contribute reusable code, features, and analytical assets to shared repositories and team standards. Benefits - Competitive compensation - Comprehensive benefits package for full-time employees, including medical, dental, and vision coverage - 401(k) with company contributions and matching - Paid parental leave - Tuition assistance - Generous paid time off - Commitment to investing in our people and supporting professional growth over time Company Description DataSpring is the trusted data connector at the core of healthcare. For more than 25 years, we have powered the industry with the largest and most complete healthcare data foundation in the U.S., including more than 4.8 million provider data records sourced directly from providers and member data representing 75% of covered lives supplied by health plans. By improving how essential information flows across the system, DataSpring helps healthcare operate more efficiently, accurately, and with greater confidence.