Senior Manager, Medical Data Science at EVYD Technology

Jerudong, , Brunei -

Full Time

Start Date

Immediate

Expiry Date

14 Jun, 26

Salary

0.0

Posted On

16 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Statistical Modeling, Machine Learning, Healthcare Analytics, Predictive Risk Models, Population Segmentation, Outcome Measurement, Data Interpretation, Mentoring, Data Logic Design, Modeling Methodology, Data Engineering Collaboration, Best Practices Documentation, Model Performance Monitoring, Clinical Relevance, Stakeholder Engagement, Python

Industry

Software Development

Description

Senior Manager, Medical Data Science What will you do? The Senior Manager, Medical Data Science, leads the development and application of advanced analytics and predictive modeling capabilities across EVYD’s digital health and population health solutions. Reporting to the Head of Medical, this role is responsible for translating structured healthcare data into deployable analytics frameworks and predictive models that demonstrate measurable clinical, operational, and economic value. The role works closely with the Medical Advisory, Medical Data Specialists, Product, Engineering, and Business Intelligence teams to ensure analytics outputs are clinically credible, technically robust, and effectively integrated into EVYD’s products and reporting solutions. Your key responsibilities include: 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. Travel requirements This role will require occasional travel, up to 20% of the time, to meet our clients and stakeholders in our countries of business. What skills do you need? 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. Qualifications 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

This role leads the development and application of advanced analytics and predictive modeling for digital and population health solutions, translating structured healthcare data into deployable analytics frameworks and predictive models that show measurable value. Key duties include leading the design and validation of risk models, supervising data specialists, and establishing internal modeling best practices.