Role Description Design, develop, and program methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. - Interact with product and service teams to identify questions and issues for data analysis and experiments. - Develop and code software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources. - Identify meaningful insights from large data and metadata sources; interpret and communicate insights and findings from analysis and experiments to product, service, and business managers. - May telecommute. Qualifications - Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical field. - 8 years of progressive, post-baccalaureate experience in the job offered or in a data scientist-related occupation. Requirements - Mathematics using principles including Calculus, Linear Algebra, Graph Theory, and Discrete Math. - Probability and statistics using principles including probability distribution, standard deviation, Bayesian and frequentist Statistics, and Dimension Reduction. - Programming languages including Python, SQL, Java, and Scala. - Tools including PySpark, Keras, Scikit-Learn, Pandas, Tensorflow, and Huggingface. - Time-Series Analysis. - Natural Language Processing (NLP). - A/B Testing. - Machine Learning. - Predictive Data Analytics. Benefits - Flexible medical, life insurance, and retirement options. - Opportunities for community involvement through volunteer programs. Company Description Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. With AI embedded across our products and services, we help customers turn that promise into a better future for all. True innovation starts when everyone is empowered to contribute. We’re committed to growing a workforce that promotes opportunities for all. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law.

• Build predictive and statistical models on real-world healthcare data, with guidance from senior data scientists and clinical input • Help craft robust, production-ready models and pipelines that meet business and clinical objectives • Support the design and analysis of A/B tests and studies, validating results against clinical reality • Acquire, clean, and transform large, messy clinical and claims datasets using SQL and modern data tooling • Partner closely with our Clinical team and clinical SMEs to understand workflows, define labels, and validate that models make clinical sense • Craft clear visualizations, reports, and presentations that turn analysis into action for clinical and business audiences

• Diseñar y construir pipelines de datos que alimenten los flujos de entrenamiento e inferencia de ML. • Desarrollar, evaluar e iterar modelos de machine learning y estadísticos orientados a soluciones de negocio. • Gestionar el ciclo de vida completo del modelo: desarrollo, validación, despliegue y monitoreo. • Colaborar con stakeholders para traducir problemas complejos de negocio en soluciones funcionales de ciencia de datos. • Documentar el trabajo con claridad suficiente para que pueda ser mantenido y extendido por el equipo. • Desplegar modelos en entornos de producción garantizando confiabilidad, rendimiento y mantenimiento del sistema.

• Curate measurement of client websites from intention to technical execution. • Consult on the ecosystems that empower and participate in data collection strategy. • Translate impact of implementation and down-funnel results, serving as connective tissue between technical implementation and end user behaviors. • Champion a data-driven culture by translating complex analytics concepts—such as server-side tracking, identity resolution, and signal loss—into accessible, actionable insights for non-technical stakeholders and executive leadership. • Create and maintain standardized documentation, best-practice guides, and playbooks that empower marketing and cross-functional teams to leverage web analytics and data enrichment tools effectively. • Assist with the monitoring and maintenance of data pipelines, ensuring that signals are flowing accurately from client environments to internal systems. • Support the integration of 1P (first-party) data solutions, helping to bridge the gap between client data warehouses and marketing platforms. • Manage user access and permissions for technical tools, ensuring data security and compliance with company protocols. • Prioritize and resolve technical tickets, troubleshooting pixel/macro implementations and cloud app issues (Jira, Google Workspace) to ensure operational uptime. • Partner with Marketing and Sales to provide feed strategy guidance and data enrichment insights. • Assist and support both internal and external needs investigating issues, executing tagging functions where needed, and helping QA. • Diagnose and resolve common technical issues by following established processes, escalating complex feed or API issues as needed. • Actively document recurring feed errors and solutions to enhance team knowledge and improve future troubleshooting. • Demonstrate a desire to learn and grow within the signal enrichment field, proactively staying updated on industry trends and platform changes. • Incorporate A.I. tools into daily workflows to boost efficiency and automate manual, repetitive tasks.