EVYD Technology - Senior Manager, Medical Data Science
Requirements
• This role will require occasional travel, up to 20% of the time, to meet our clients and stakeholders in our countries of business. • Core Competencies • Strong foundation in statistical modeling, machine learning, and applied healthcare analytics. • Ability to translate complex analytical findings into clear, stakeholder-ready insights. • Experience operationalizing analytics solutions within real-world healthcare systems. • Strong leadership capability with experience mentoring technical teams. • Systems-level thinking and ability to operate effectively in complex healthcare environments. • Effective communication skills across technical, clinical, and commercial audiences. • Bachelor’s or master's degree in data science, biostatistics, statistics, computer science, health informatics, applied mathematics, or a related quantitative discipline. • Typically 8–10 years of experience in healthcare analytics, medical data science, or applied machine learning within healthcare, public health, or HealthTech environments. • Demonstrated experience leading analytics or data science teams. • Strong hands-on capability in analytics prototyping and technical review; experience with common data science tools and programming languages (e.g., Python, R, SQL) is highly desirable. • Experience working with electronic medical records, registries, claims data, or digital health datasets. • Experience demonstrating outcomes measurement and value articulation to healthcare stakeholders is highly desirable. • An advanced degree (PhD, MPH, or equivalent) is an advantage but not mandatory. • Strong written and verbal communication skills in English.
Responsibilities
• Lead the design, development, validation, and continuous improvement of predictive risk models, population segmentation algorithms, and outcome measurement frameworks. • Translate healthcare datasets into deployable analytics solutions that support EVYD’s digital health platforms and population health programs. • Define analytical metrics, outcome frameworks, and reporting logic to support dashboards and reporting solutions delivered through Business Intelligence and product teams. • Interpret modeling outputs and translate analytical findings into actionable insights for clinical, operational, and strategic decision-making. • Supervise and mentor medical data specialists and medical data scientists, ensuring high standards in data logic design, modeling methodology, reproducibility, documentation, and overall technical quality. • Work closely with medical data specialists to define analytical datasets, data logic, and extraction requirements required for modeling and analytics initiatives. • Collaborate with data engineering teams to operationalize analytics workflows while data engineering retains ownership of data pipelines and infrastructure. • Establish internal modeling best practices, documentation standards, and analytical methodologies within the Medical Data Science team. • Monitor model performance, bias, and drift, ensuring continuous improvement and responsible analytics practices. • Collaborate closely with Medical Advisory to ensure the clinical relevance, interpretability, and defensibility of analytics outputs. • Support commercial and stakeholder engagements by clearly articulating the methodology, robustness, and value of analytics-driven solutions. • Develop and scale the medical data science team in alignment with organizational growth plans.
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