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About Improzo At Improzo ( Improve + Zoe; meaning Life in Greek ), we believe in improving life by empowering our customers. Founded by seasoned Industry leaders, we are laser focused on delivering quality-led commercial analytical solutions to our clients. Our dedicated team of experts in commercial data, technology, and operations has been evolving and learning together since our inception. Here, you won't find yourself confined to a cubicle; instead, you'll be navigating open waters, collaborating with brilliant minds to shape the future. You will work with leading Life Sciences clients, seasoned leaders and carefully chosen peers like you! People are at the heart of our success, so we have defined our CARE values framework with a lot of effort, and we use it as our guiding light in everything we do. We CARE! Customer-Centric: Client success is our success. Prioritize customer needs and outcomes in every action. Adaptive: Agile and Innovative, with a growth mindset. Pursue bold and disruptive avenues that push the boundaries of possibilities. Respect: Deep respect for our clients & colleagues. Foster a culture of collaboration and act with honesty, transparency, and ethical responsibility. Execution: Laser focused on quality-led execution; we deliver! Strive for the highest quality in our services, solutions, and customer experiences. About The Role We are seeking a highly motivated RWE-HEOR-Patient Analytics Specialist at the Associate Consultant/Senior Associate Consultant/Consultant/Senior Consultant level to join our dynamic team. In this role, you will play a critical part in leveraging Patient Analytics, Real-World Evidence (RWE) and Health Economics & Outcomes Research (HEOR) methodologies to drive impactful insights and support life sciences clients in optimizing patient outcomes, decoding patient journeys and refining healthcare strategies. You will apply advanced analytical techniques to generate evidence, drive patient-centric insights, influence healthcare decision-making, and support market access strategies. Key Responsibilities Patient Journey Analytics & Segmentation: Lead comprehensive patient journey mapping initiatives, utilizing advanced analytics to identify patient phenotypes, treatment pathways, adherence patterns, and care gaps across diverse therapeutic areas. Predictive Patient Modeling: Develop and deploy machine learning models for patient risk stratification, treatment response prediction, and personalized care pathway optimization using multi-modal healthcare data sources. Patient-Reported Outcomes Analysis: Design and execute sophisticated analyses of patient-reported outcomes (PROs), quality of life measures, and patient satisfaction data to quantify treatment impact from the patient perspective. Real-World Data Integration & Patient Cohort Development: Apply advanced statistical modeling and epidemiological methods to analyze claims data, EMRs, wearable device data, and patient registries with a focus on patient-level insights and longitudinal patient analytics. Health Economics Through Patient Lens: Conduct patient-centered economic evaluations, including cost-per-patient analyses, patient lifetime value modeling, and healthcare resource utilization studies to support value-based care initiatives. Advanced Patient Analytics Solutions: Lead the design and implementation of AI/ML applications for patient behavior prediction, treatment optimization algorithms, and patient engagement analytics to inform precision medicine strategies. Client Engagement & Patient-Centric Strategy: Collaborate with clients to translate patient analytics insights into actionable healthcare strategies, focusing on patient outcomes improvement, care personalization, and patient experience enhancement. Stakeholder Communication & Patient Advocacy: Effectively communicate patient-centered research findings to healthcare providers, payers, pharmaceutical companies, and patient advocacy groups through compelling visualizations, reports, and presentations. Project Leadership & Innovation: Manage complex patient analytics projects end-to-end while fostering innovation in patient data science methodologies and contributing to thought leadership in patient analytics. Team Development & Knowledge Sharing: Mentor team members in patient analytics techniques and contribute to internal capability building in patient-centered research methodologies. Qualifications Education: Bachelor's or Master's degree in Data Science, Biostatistics, Health Informatics, Digital Health, Epidemiology, Health Economics, Public Health, or related quantitative fields with emphasis on patient-centered research. Experience 3-9 years of experience in Patient Analytics, Digital Health Analytics, RWE and HEOR, preferably within the pharmaceutical, consulting, or healthcare industries. Technical Skills Advanced proficiency in statistical software and programming languages (Python, R, SAS, SQL) with emphasis on patient data analysis. Expert-level application of machine learning (scikit-learn, TensorFlow, PyTorch) in patient stratification, cost-effectiveness modeling, and real-world outcomes analytics. Proficiency in advanced data visualization tools (Tableau, Power BI, Python/R visualization libraries) for patient journey visualization and patient outcomes dashboards. Experience with healthcare databases (claims, EHR, patient registries, wearable data) and patient data integration techniques. Knowledge of patient privacy regulations (HIPAA, GDPR) and healthcare data security protocols. Proficient in leveraging clinical trial data, patient-reported outcomes platforms, and digital health technologies for real-world evidence generation and HEOR insights. Analytics Skills Experience with patient cohort identification and matching algorithms. Knowledge of patient engagement analytics and behavioral health analytics. Understanding of care pathway optimization and treatment sequence analysis. Familiarity with patient risk scoring and population health management. Experience to integrate Real-World Evidence (RWE) and Health Economics & Outcomes Research (HEOR) principles Personal Skills Patient-centric mindset with strong analytical and problem-solving abilities focused on improving patient outcomes. Excellent communication skills with ability to translate complex patient analytics into actionable insights for clinical and business stakeholders. Collaborative approach to working with clinical teams, data scientists, and healthcare professionals. Adaptability and continuous learning mindset to stay current with patient analytics innovations, RWE and HEOR trends. Ethical approach to patient data handling and commitment to patient privacy and data security. Benefits Competitive salary and comprehensive benefits package Leadership opportunities in cutting-edge patient analytics, RWE and HEOR initiatives Career development in the rapidly growing patient analytics and precision medicine field Collaborative environment with opportunities to directly impact patient care and outcomes Exposure to innovative healthcare technologies and global life sciences industry trends Professional development support including conferences, certifications, and advanced training in patient analytics, RWE and HEOR methodologies Skills: real-world evidence (rwe),health economics & outcomes research (heor),heor,predictive analytics,patient-reported outcomes,rwe,analytics,patient data integration,predictive modeling,machine learning,rwd,apld,patient analytics,advanced analytics,data visualization,healthcare,statistical modeling Show more Show less
