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Data Scientist - Job Opportunity at RLDatix

Richmond, United Kingdom
Full-time
Mid-level
Posted: May 27, 2025
Hybrid
£55,000 - £75,000 per year based on UK market rates for mid-level data scientists in healthcare technology, with potential for higher compensation given the specialized healthcare domain knowledge and LLM expertise requirements

Benefits

Flexible work arrangements that enable work-life balance and accommodate diverse working styles, positioning the company as a progressive employer in the competitive tech talent market
Employee wellness prioritization demonstrating comprehensive health and mental well-being support, which is increasingly valued by data science professionals
Global collaboration opportunities across international teams, providing exposure to diverse healthcare markets and cross-cultural professional development
Mission-driven work environment focused on healthcare safety transformation, offering meaningful career purpose beyond traditional tech roles

Key Responsibilities

Design and develop sophisticated machine learning models, large language models, and algorithms that directly impact healthcare decision-making and patient safety outcomes across global healthcare systems
Establish and maintain critical ETL workflows and data pipelines that serve as the foundation for enterprise-wide data consistency, ensuring scalable and reliable data infrastructure for healthcare operations
Optimize machine learning models and AI systems to achieve maximum performance and real-world accuracy, directly contributing to the safety and efficiency of healthcare delivery worldwide
Translate complex data science concepts into actionable business insights, serving as a strategic bridge between technical capabilities and organizational decision-making processes
Lead cross-functional collaboration with engineering, QA, and product teams to align advanced analytics solutions with business objectives and healthcare industry requirements

Requirements

Education

A bachelor's or master's degree in computer science, Data Science, AI, Software Engineering, or a related field is preferred

Experience

3+ years of experience in a data-science related role, with hands-on experience in data science engineering

Required Skills

Proficiency in programming languages such as Python and SQL Experience with data processing and analysis tools and technologies like TensorFlow, Keras, Scikit-learn Strong understanding of large language models (LLMs) and machine learning (ML) algorithms and techniques Familiarity with data visualization tools such as Power BI Solid understanding of statistical analysis and hypothesis testing Ability to work with structured and unstructured data sources Knowledge of cloud computing platforms (AWS, Azure) and data security measures, including compliance with data governance standards and big data technologies Experience with Databricks and Mosaic AI is plus
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Sauge AI Market Intelligence

Industry Trends

Healthcare technology is experiencing unprecedented growth driven by digital transformation initiatives, with healthcare analytics market projected to reach $84.2 billion by 2027, creating massive demand for data scientists who can navigate complex healthcare data landscapes and regulatory environments. Large Language Models and AI are revolutionizing healthcare operations through clinical decision support systems, predictive analytics for patient outcomes, and automated medical documentation, positioning LLM-experienced data scientists at the forefront of industry innovation. Healthcare data governance and compliance requirements are becoming increasingly stringent with regulations like GDPR, HIPAA, and emerging AI governance frameworks, making data scientists with healthcare compliance knowledge extremely valuable in the market. Cloud-first healthcare infrastructure adoption is accelerating, with major providers migrating to AWS, Azure, and specialized healthcare clouds, driving demand for data scientists skilled in cloud-native analytics platforms and healthcare-specific data security measures.

Role Significance

Likely part of a 5-8 person Data Platform team within a larger engineering organization, with responsibility for mentoring junior data scientists and collaborating across multiple product and engineering teams in a matrix organizational structure
This is a mid-to-senior level position with significant technical leadership responsibilities, evidenced by the requirement to lead model development, establish enterprise data pipelines, and serve as a technical liaison with cross-functional teams, indicating substantial autonomy and strategic impact on organizational data capabilities

Key Projects

Development of predictive models for patient safety risk assessment and early warning systems that can prevent adverse healthcare events Implementation of large language models for clinical documentation automation and medical text analysis to improve healthcare operational efficiency Creation of real-time healthcare operations dashboards and analytics platforms that enable data-driven decision making for healthcare administrators and clinicians Design of machine learning pipelines for healthcare quality metrics analysis and regulatory compliance reporting

Success Factors

Deep understanding of healthcare domain complexities including clinical workflows, regulatory requirements, and patient safety protocols, which is essential for developing relevant and compliant analytics solutions Strong technical versatility across traditional machine learning, modern deep learning frameworks, and emerging LLM technologies, enabling adaptation to rapidly evolving healthcare AI landscape Exceptional communication and stakeholder management skills to translate complex technical concepts into actionable business insights for healthcare professionals and executives Experience with enterprise-scale data engineering and MLOps practices to ensure robust, scalable, and maintainable analytics solutions in mission-critical healthcare environments

Market Demand

Very High - Healthcare data science roles are experiencing exceptional demand due to industry digitization, regulatory requirements for data-driven healthcare improvements, and the critical shortage of professionals who understand both advanced analytics and healthcare domain complexities

Important Skills

Critical Skills

Python and SQL proficiency is absolutely essential as these form the foundation of modern data science workflows, with Python being the dominant language for machine learning and SQL being critical for healthcare data extraction and analysis Machine learning frameworks like TensorFlow, Keras, and Scikit-learn are fundamental for developing the predictive models and AI systems that drive healthcare decision-making and patient safety improvements Large Language Model understanding is increasingly critical as healthcare organizations adopt AI for clinical documentation, medical text analysis, and decision support systems Cloud platform knowledge (AWS, Azure) is essential for scalable healthcare analytics, especially given the industry's migration to cloud infrastructure and the need for compliant, secure data processing

Beneficial Skills

Databricks and Mosaic AI experience provides competitive advantage for advanced MLOps and collaborative data science workflows in enterprise healthcare environments Healthcare domain knowledge and understanding of clinical workflows accelerates effectiveness and reduces learning curve in healthcare-specific analytics applications Data governance and compliance expertise becomes increasingly valuable as healthcare AI regulation evolves and organizations need to ensure ethical, compliant AI implementations Advanced statistical analysis and hypothesis testing skills enable rigorous validation of healthcare interventions and support evidence-based healthcare improvement initiatives

Unique Aspects

Direct impact on global patient safety through data science applications, offering rare opportunity to apply advanced analytics to life-saving healthcare improvements
Exposure to large language models in healthcare context, positioning for cutting-edge AI applications in clinical and operational settings
Combination of technical data science leadership with healthcare domain expertise, creating valuable niche specialization in high-demand market
Global collaboration opportunities across diverse healthcare markets, providing international perspective on healthcare data challenges and solutions

Career Growth

2-4 years to senior individual contributor roles, 3-5 years to management positions, with accelerated progression possible given the high demand for healthcare AI expertise and the mission-critical nature of healthcare data science applications

Potential Next Roles

Senior Data Scientist or Principal Data Scientist roles with expanded technical leadership and strategic planning responsibilities Data Science Manager or Head of Analytics positions leading larger teams and setting organizational data strategy Healthcare AI Product Manager roles leveraging domain expertise to drive product development in health tech companies Chief Data Officer or VP of Analytics positions in healthcare organizations or health tech startups

Company Overview

RLDatix

RLDatix is a established healthcare technology company specializing in healthcare risk management and patient safety solutions, serving healthcare organizations globally with a focus on connecting data to improve healthcare outcomes and operational efficiency

Well-positioned as a specialized healthcare technology provider with a strong focus on patient safety and quality improvement, competing in the growing healthcare operations and risk management software market
This UK-based role suggests RLDatix has significant European operations while maintaining global reach, offering opportunities to work on international healthcare challenges while being positioned in London's thriving health tech ecosystem
Mission-driven culture focused on meaningful healthcare impact, with emphasis on collaboration, flexibility, and employee wellness, typical of mature health tech companies that balance purpose-driven work with competitive employee benefits
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