Senior Data Scientist

HeliosX

HybridPosted 28 июля 2026 г.

About the role

HeliosX is seeking a Senior Data Scientist to shape the future of personalised digital healthcare by building and deploying advanced recommendation models that turn real-world patient data into actionable insights, improving outcomes and engagement. You will work with Product, clinical teams, and engineers to design data-driven solutions using a modern stack (Snowflake, Hex, Claude) to deliver truly individualised care at scale. This is a full-time, hybrid role based in London (Shoreditch), requiring on-site presence twice per week with the option to work remotely the remaining days.

Senior Data Scientist

HeliosX

HybridPosted 28 июля 2026 г.

About the role

HeliosX is seeking a Senior Data Scientist to shape the future of personalised digital healthcare by building and deploying advanced recommendation models that turn real-world patient data into actionable insights, improving outcomes and engagement. You will work with Product, clinical teams, and engineers to design data-driven solutions using a modern stack (Snowflake, Hex, Claude) to deliver truly individualised care at scale. This is a full-time, hybrid role based in London (Shoreditch), requiring on-site presence twice per week with the option to work remotely the remaining days.

Responsibilities

Clinical Prediction Models: design and implement ML models predicting outcomes such as treatment response, adherence, adverse events, and clinical deterioration
Patient Stratification: build risk stratification models to identify patients who would benefit from interventions or enhanced monitoring
Treatment Optimization: develop models recommending optimal treatment pathways and personalized clinical interventions
Healthcare ML Best Practices: ensure models are interpretable, validated, and compliant with regulatory guidance
Product-Embedded Analytics: lead integration of ML models into features that improve medication management and adherence
Patient Journey Optimization: personalize experiences across online consultations, prescriptions, and ongoing management
Real-Time Clinical Insights: develop streaming ML capabilities for real-time risk alerts
Cross-Functional Leadership: partner with product, clinical teams, and engineers to translate model insights int

Responsibilities

Clinical Prediction Models: design and implement ML models predicting outcomes such as treatment response, adherence, adverse events, and clinical deterioration
Patient Stratification: build risk stratification models to identify patients who would benefit from interventions or enhanced monitoring
Treatment Optimization: develop models recommending optimal treatment pathways and personalized clinical interventions
Healthcare ML Best Practices: ensure models are interpretable, validated, and compliant with regulatory guidance
Product-Embedded Analytics: lead integration of ML models into features that improve medication management and adherence
Patient Journey Optimization: personalize experiences across online consultations, prescriptions, and ongoing management
Real-Time Clinical Insights: develop streaming ML capabilities for real-time risk alerts
Cross-Functional Leadership: partner with product, clinical teams, and engineers to translate model insights int

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