About The Company
Resilience Care is a pioneering French company specializing in remote patient monitoring (RPM) solutions and serving as a trusted partner in clinical research. Established in 2021, the company's mission centers around delivering better, more personalized patient care through innovative technology. Resilience Care offers comprehensive RPM solutions across oncology, gastroenterology, and psychiatry, integrating electronic Patient-Reported Outcomes (ePRO) collection with advanced AI techniques. The platform empowers healthcare professionals by enabling early detection of side effects, facilitating continuous and proactive patient management. Additionally, the company's mobile app enhances patient engagement by providing tailored resources to help measure and manage symptoms effectively.
With a focus on improving care pathways, enriching continuous patient understanding, and accelerating clinical research, Resilience Care collects, structures, and analyzes real-world data to generate actionable insights. Currently, its solutions are deployed in routine care for over 35,000 patients across more than 200 healthcare institutions and support around twenty academic and industry-led clinical studies. The company's core philosophy revolves around putting data at the service of care and therapeutic innovation, aiming to enable every patient to benefit from personalized medicine.
About The Role
As a Data Scientist at Resilience Care, you will be instrumental in designing and deploying machine learning models based on real-world patient health data. Your primary focus will be supporting Medical Affairs studies and developing emerging product capabilities to shape the future development of Resilience's innovative platform. Your work will directly impact how healthcare professionals interpret patient data, enabling more accurate predictions, early intervention, and personalized treatment plans.
In this role, you will bring your expertise in machine learning methodologies to develop reliable models that generate actionable insights for Medical Affairs and Product teams. Working in a dynamic scale-up environment, your contributions will help scale the company's solutions while maintaining high standards of quality and reliability. You will collaborate closely with medical and product teams to understand their needs, communicate methodological choices clearly, and contribute to the continuous improvement of healthcare ML applications. Your efforts will also include establishing validation strategies, automating recalculations, and monitoring model performance to ensure robustness and clinical relevance.
By contributing to applied healthcare ML research and practical improvements, you will play a key role in advancing the company's mission of improving patient outcomes through data-driven innovations. This position offers an exciting opportunity to work at the intersection of data science, healthcare, and clinical research, making a tangible difference in patient lives and the future of personalized medicine.
Qualifications
- 3–5 years of experience in Data Science or a related field
- Proficiency in Python and/or R programming languages
- Experience with SQL for data extraction and preparation
- Strong understanding of machine learning methodologies applied to healthcare datasets
- Experience handling longitudinal and repeated-measures data, including mixed-effects models
- Ability to set up scoring, recalculation pipelines, and basic monitoring systems
- Excellent communication skills to explain assumptions, limitations, and results clearly and inclusively
- Demonstrated ownership, autonomy, and a proactive learning mindset
- Strong problem-solving skills, tenacity, and the ability to manage multiple topics simultaneously
- Flexibility and adaptability within a scale-up environment
- Experience working with non-technical stakeholders to scope and deliver outcomes
Responsibilities
- Design and develop predictive machine learning models on real-world patient datasets for Medical Affairs studies
- Work with longitudinal and repeated-measures data using appropriate analytical approaches
- Define validation strategies and performance metrics aligned with clinical and real-world constraints
- Automate model recalculations, scoring, scheduling, and monitoring to ensure operational efficiency
- Collaborate with Medical and Product teams to understand their needs and communicate methodological choices effectively
- Contribute to healthcare ML watch initiatives, proposing practical improvements based on emerging trends
- Build and maintain scoring pipelines, ensuring robustness and scalability
- Document assumptions, limitations, and results in a clear, transparent manner for diverse stakeholders
- Participate in cross-functional discussions to align data science solutions with clinical and product objectives
Benefits
- Opportunity to work at the forefront of healthcare innovation and data-driven patient care
- Collaborative and dynamic work environment within a scale-up setting
- Engagement in high-impact projects that directly improve patient outcomes and clinical research efficiency
- Development of advanced skills in healthcare machine learning and real-world data analysis
- Exposure to multidisciplinary teams including medical, pharma, and technical experts
- Flexible working arrangements supporting work-life balance
- Potential for career growth within a rapidly expanding company
Equal Opportunity
Resilience Care is committed to fostering an inclusive and diverse workplace. We are an equal opportunity employer and welcome applications from individuals of all backgrounds, regardless of race, gender, age, sexual orientation, disability, or any other characteristic protected by applicable law. We believe that diverse teams drive innovation and excellence, and we strive to create an environment where everyone can thrive and contribute to our mission of improving patient care through data-driven solutions.