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Data Scientist, Biostatistics & RWE
About Every Cure -
Every Cure is an AI-driven nonprofit, biotech organization that was founded to uncover and repurpose existing drugs to treat the millions of patients who suffer from diseases without approved treatments. By focusing on drug repurposing, we aim to provide affordable and accessible therapies for those suffering from diseases that are often overlooked in traditional drug development. Through artificial intelligence technologies, collaboration with healthcare professionals, and patient advocacy, Every Cure is dedicated to unlocking the full potential of existing medicines to treat every disease and every patient we possibly can. Inspired by Every Cure’s co-founders' work repurposing drugs for Castleman disease and other rare diseases, Every Cure has advanced repurposed treatments for neglected diseases and been featured in USA Today, Good Morning America, and Wall Street Journal. Led by a talented leadership team and an outstanding Board of Directors, Every Cure is supported through funding from leading philanthropic organizations like Chan Zuckerberg Initiative and Elevate Prize Foundation and a federal contract with ARPA-H.
Our approach -
- AI-Powered Identification: We use advanced artificial intelligence to analyze the world’s biomedical knowledge and identify FDA-approved drugs that can be repurposed for untreated conditions. This cutting-edge technology enables us to explore new therapeutic possibilities efficiently.
- Open-Source Commitment: We are dedicated to making our predictive pipeline open-source, fostering collaboration and transparency within the scientific community and unlocking the potential for discovering new treatments.
- High-Impact Focus: We prioritize drug repurposing opportunities that can benefit neglected patient communities, ensuring our efforts address the most pressing needs.
- Rigorous Validation: Promising opportunities are thoroughly validated through laboratory and clinical studies to confirm their efficacy and safety before advancing to broader application.
- Equitable Access: We are committed to ensuring that new cures are accessible to all patients, regardless of geographic or economic barriers.
We are seeking a Data Scientist with expertise in Real-World Evidence (RWE), biostatistics, and epidemiology to drive rigorous analysis of clinical, claims, electronic health records (EHR), and observational healthcare data. You will collaborate with cross-functional teams to support drug repurposing decisions, perform systematic evidence synthesis, and apply advanced statistical methodologies to generate high-impact insights.
How you’ll make an impact -
- Analyze & Deliver: Conduct epidemiological and biostatistical analyses on integrated real-world data (e.g., EHR, claims, registries, patient-reported outcomes) to assess treatment effects, disease burden, and real-world effectiveness. Deliver outputs such as study reports and high-impact analyses.
- Synthesize Evidence: Perform meta-analyses and systematic reviews of clinical and observational studies to inform drug repurposing strategies.
- Innovate & Optimize: Design and implement non-interventional studies using causal inference methods such as propensity score matching, inverse probability weighting, and difference-in-differences.
- Model Development: Develop and execute statistical analysis plans using Bayesian modeling, survival analysis, mixed-effects modeling, and time-series forecasting. Apply machine learning techniques to high-dimensional patient-level data for predictive modeling.
- Collaborate: Partner with clinicians, data scientists, and medical teams to ensure analytical outputs align with drug repurposing goals.
- Ensure Rigor & Reproducibility: Stay current with evolving RWE regulatory guidelines and data standards to uphold the validity and transparency of real-world evidence generation.
What you’ll bring to the team -
- Education & Experience
- Advanced degree (Ph.D. or Master’s) in Epidemiology, Biostatistics, Public Health, or a related quantitative field is a plus.
- Experience in observational study design, causal inference, and advanced statistical modeling for healthcare data.
- Experience working with health economics and outcomes research, or real-world evidence is a plus.
- Experience conducting trial designs is a plus.
- Technical Expertise
- Strong foundation in statistical analysis, predictive modeling, and observational data analytics.
- Proficiency in statistical programming (e.g., R, Python, SAS) for data analysis and model development.
- Expertise in meta-analysis, time-to-event analysis, Bayesian approaches, and sensitivity analysis.
- Familiarity with real-world data sources (e.g., claims, EHR, registries, digital health) and data standards (e.g., OMOP).
- Working knowledge of machine learning for healthcare applications and advanced analytics for patient stratification is a plus.
- Other Skills
- Strong problem-solving abilities with the ability to translate complex data into actionable insights.
- Excellent communication skills to engage both technical and non-technical stakeholders.
- Passion for leveraging data science to advance biomedical research and improve patient outcomes.
Compensation & Benefits -
- Your paycheck: Competitive salary based on experience, ranging from £50,000 - £80,000 annually.
- Health and wellness: Comprehensive plans with medical, dental, and vision coverage, administered by Bupa.
- Future nest egg: A pension plan with an employer match of 3% helps you save for your future.
- Relax and recharge: Generous time off, including paid holidays.
- We have you covered: Comprehensive life and income protection administered by Unum, ensuring you have the support you need during important times.
This role is based in London with an expectation of minimum 3 days per week in office.
Every Cure is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We provide equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, or any other characteristic protected by federal, state, or local laws.
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