Data Scientist

About Qureight

Qureight is dedicated to expediting clinical trials, particularly in lung and heart diseases, so that significant medical breakthroughs reach patients faster. Utilizing an AI-enhanced platform for data and imaging management, the company supports extensive analysis of clinical imaging and other healthcare-related datasets to assist customers in accelerating treatment development.

Operating out of Cambridge and London, the team is composed of clinicians, scientists, and engineers united by a culture of openness, continuous learning, and a shared goal of enabling smarter, faster biopharma trials.

Role Overview

The Data Scientist will join Qureight's innovative data science team to play a key role in analyzing complex datasets drawn from research projects, clinical trials, and client studies. The position involves collaborating closely with pharmaceutical partners and research organizations worldwide to design impactful statistical models focused on lung disease.

Key Responsibilities

• Provide expert statistical guidance across clinical study design, trial analyses, and business initiatives.
• Develop and sustain robust data pipelines, statistical analyses, machine learning workflows, and visualization tools for experimental and clinical research.
• Apply both supervised and unsupervised machine learning methods, including predictive modelling and clustering, to extract insights from increasingly large and complex clinical and real-world datasets.
• Enhance and define statistical analysis processes in cooperation with stakeholders and healthcare professionals.
• Create and present protocols, analysis reports, presentations, and other documents to effectively share findings with clients and stakeholders.
• Contribute to scientific dissemination through preparing abstracts, posters, conference presentations, and publications as needed.
• Participate as a creative collaborator within a multidisciplinary team, promoting novel solutions aligned with the company’s mission.

Qualifications and Requirements

• Minimum 2 years of professional experience in applied data science.
• Strong knowledge of probability and statistics, including power/sample size determination, hypothesis testing, parametric/non-parametric techniques, and survival analysis such as Cox regression and Kaplan-Meier estimation.
• Demonstrated expertise in applying statistical techniques to real-world datasets, particularly clinical trial data within pharma or CRO contexts.
• Proficiency with regression methods (linear, logistic) for inference and prediction, including use of cross-validation, regularization (L1/L2), feature selection, and model evaluation metrics like AUC, precision, recall, and calibration.
• Experience implementing machine learning strategies for classification, prediction, and clustering, with the ability to select, validate, and assess appropriate models.
• Excellent communication skills with the ability to clearly convey complex analytical results to diverse audiences including clients and clinicians.
• Ability to develop scientific communications including abstracts, posters, presentations, and manuscripts.
• Advanced Python skills, including use of libraries such as Pandas, Jupyter, Scikit-learn, NumPy, SciPy, Matplotlib, Seaborn, and Plotly.
• Capable of writing clean, modular, and efficient code with best practices, including version control (Git), documentation, error handling, testing, and memory management.
• Expertise in managing and cleaning large datasets.

Preferred Skills

• Experience with advanced statistical models, such as mixed-effects modeling.
• Familiarity with techniques to generate synthetic clinical trial arms using matching methods.
• Comfort with command-line interface tools.
• Experience working with cloud infrastructure, particularly AWS.

Education

A degree in statistics, mathematics, or a closely related quantitative or scientific discipline is required.

Benefits

• Competitive benefits package including an annual bonus, private medical and life insurance, and contributory pension scheme.
• 25 days of paid annual leave, plus bank holidays and enhanced maternity leave.
• An inclusive and diverse working environment that integrates experts across fields such as software engineering, DevOps, data science, machine learning, quality assurance, regulatory affairs, and clinical operations.

Equal Opportunity and Application Process

Qureight welcomes applications from candidates of all backgrounds, committed to equal opportunity employment, encouraging individuals irrespective of age, disability, ethnicity, gender identity, religion, sexual orientation, or other protected statuses to apply.

Candidates from underrepresented groups are encouraged to apply even if they do not meet all qualifications, as the company values diverse perspectives. Reasonable adjustments to the selection process are provided upon request to support all applicants.