• Diseñar modelos analíticos y seleccionar técnicas, variables, codificaciones y algoritmos adecuados. • Desarrollar el código de los modelos y asegurar su correcto funcionamiento. • Analizar grandes volúmenes de datos para generar insights y apoyar decisiones informadas. • Identificar relaciones entre variables y construir soluciones basadas en analítica descriptiva, predictiva y prescriptiva. • Optimizar modelos para asegurar escalabilidad, repetitividad y eficiencia. • Apoyar el roadmap de modelos y actividades analíticas junto con el líder del equipo. • Liderar el monitoreo, mantenimiento y actualización de los modelos implementados. • Co-liderar el despliegue de modelos en ambientes tecnológicos internos junto con Arquitectura de Datos. • Guiar técnicamente a otros científicos de datos del equipo.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description DeepIntent is seeking an experienced Senior Director of Data Science to help lead our global data science organization and advance the next generation of data innovation in healthcare advertising technology. In this role, you will lead a team focused on advanced modeling, optimization, and AI initiatives that enable healthcare marketers to connect patients, providers, and brands responsibly and effectively. The Senior Director, Data Science will help shape and execute data science initiatives that drive predictive, privacy-safe insights to power precision marketing and measurable outcomes. This role will collaborate with data scientists across the U.S., Europe, and India while partnering closely with product, engineering, and commercial leaders to deliver scalable, data-driven solutions. Qualifications - Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field - Master’s or Ph.D. in Computer Science, Statistics, Mathematics a plus - 8+ years of experience in data science, machine learning, or advanced analytics roles - 5+ years of people management experience managing data science or analytics teams - Experience working with healthcare data, adtech platforms, or marketing analytics environments - Strong understanding of programmatic advertising, identity resolution, and healthcare data ecosystems (claims, RWD, HCP and patient data) - Advanced experience with Python, SQL, Spark, and modern machine learning frameworks (TensorFlow, PyTorch, XGBoost) - Strong foundation in statistics, causal inference, and measurement methodologies for media effectiveness and attribution - Excellent communicator capable of translating complex technical concepts to business stakeholders and clients - Experience working with healthcare compliance frameworks (HIPAA, GDPR, CCPA) and privacy-aware data science practices - Comfort working in global, cross-functional environments across multiple time zones - Passion for applying data science and AI to improve healthcare marketing outcomes Requirements - Partner with executive and cross-functional leadership to translate data science capabilities into scalable, compliant, and commercially impactful solutions - Help execute the global data science roadmap supporting DeepIntent’s mission to transform healthcare marketing through data and technology - Lead and mentor a distributed team of data scientists across the U.S., Europe, and India - Foster a culture of innovation, experimentation, and collaboration across teams - Contribute to strategic planning and help identify new opportunities where advanced analytics and AI can drive business impact - Develop and optimize predictive and causal models for patient and provider targeting, audience segmentation, and campaign performance measurement - Oversee the development and deployment of machine learning models supporting real-time bidding, healthcare audience modeling, and privacy-first identity resolution - Integrate real-world data (RWD), claims data, and digital engagement signals into scalable machine learning pipelines - Ensure models and data science practices align with healthcare privacy standards including HIPAA and other global regulatory frameworks - Collaborate with engineering, product, and data partnerships teams to strengthen our data infrastructure supporting large-scale, multi-market model deployment - Implement best practices in feature engineering, reproducible research, and ML Ops to improve experimentation speed and reliability - Partner with legal and compliance teams to ensure responsible AI development and ethical use of healthcare data - Work closely with Product, Engineering, Data Partnerships, and Commercial teams to design data-driven solutions that improve targeting precision, optimize media performance, and enhance client outcomes - Translate complex modeling outputs into actionable insights for internal stakeholders and clients Benefits - Competitive base salary range of $185,000 - $220,000 - Annualized bonus plan - Comprehensive medical, dental, and vision insurance - 401K match program - Unlimited PTO policy and paid holidays - Remote friendly culture with flexible work options - Career development and advanced education support - WFH and internet stipends - Competitive base salary plus performance-based bonus for India: comprehensive medical insurance and paid holidays - Hybrid-friendly culture with flexible work options in India - Professional development reimbursement and health and wellness allowance in India - Competitive base salary plus performance-based bonus for Europe: comprehensive medical insurance and flexible PTO - Hybrid-friendly culture with flexible work options in Europe - Professional development reimbursement and parental leave in Europe

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Designs, develops and programs 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. - Interacts with product and service teams to identify questions and issues for data analysis and experiments. - Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. - Identifies meaningful insights from large data and metadata sources. - Interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. - May telecommute. Qualifications - Master's degree in Computer Science, Engineering, Computer Information Systems or related technical field. - 5 years of experience in the job offered or in a Data Scientist-related occupation. Requirements - Java - Python - REST APIs - Microservices - Big Data including: HiveSQL, Spark, Elastic Cache, and Redis - Agile Development - Test Driven Development Junit and Selenium - Data Structures - Databases SQL and NoSQL - Distributed Systems and cloud platforms (OCI) Benefits - Flexible medical options - Life insurance - 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.

• Focus on understanding existing models, assessing their performance, selecting optimal architectures, and fine-tuning them to meet specific domain and business needs—including retrieval-augmented generation (RAG) based applications. • Collaborate closely with data engineering, product, and domain teams to translate real-world research challenges into scalable, model-driven solutions that accelerate Advarra’s vision of a digitally connected research data and technology fabric. • Optimize and fine-tune large language models (LLMs) and domain-specific variants using proprietary datasets to achieve precision and recall targets that drive differentiated customer value. • Evaluate model performance across key metrics and benchmarks, identifying strengths, weaknesses, and opportunities for improvement across predictive, generative, and retrieval-augmented tasks. • Implement and operationalize LLM-based and retrieval-augmented (RAG) systems that enhance Braid-powered products such as Study Design and Site Feasibility. • Collaborate with data engineering to ensure scalable, efficient model training, evaluation, and deployment pipelines using Databricks, MLflow, and Delta Lake. • Assess and select models—open-source or proprietary—that best align with domain-specific requirements and Advarra’s regulated research environment. • Partner with clinical and operational experts to translate research and trial challenges into measurable model evaluation frameworks and optimization strategies. • Conduct model interpretability and bias analyses to ensure fairness, transparency, and compliance with governance standards. • Document methodologies and validation results to support internal governance, reproducibility, and audit readiness. • Contribute to reusable fine-tuning workflows, evaluation frameworks, and model monitoring pipelines within the Braid AI stack. • Stay at the forefront of advancements in LLM optimization, retrieval augmentation, and multi-modal learning, applying new methods that improve scalability, explainability, and cost efficiency