National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Biostatistician (The Data-Driven Health Innovator)

Unreal Gigs
Cambridge
6 months ago
Applications closed

Do you have a passion for using data to drive advancements in healthcare, medicine, and public health? Are you excited about applying statistical methods to clinical trials, epidemiological studies, and drug development to discover new insights that can improve patient outcomes? If you’re ready to make a significant impact by analyzing complex data and providing actionable insights,our clienthas the perfect opportunity for you. We’re seeking aBiostatistician(aka The Data-Driven Health Innovator) to analyze and interpret health data, driving critical decisions in clinical trials, medical research, and healthcare strategy.

As a Biostatistician atour client, you will collaborate with clinical researchers, data scientists, and regulatory teams to provide statistical expertise throughout the entire lifecycle of medical research. From study design to data analysis and interpretation, your work will play a pivotal role in ensuring that clinical trials are scientifically sound, data-driven, and aligned with regulatory requirements.

Key Responsibilities:

  1. Design and Analyze Clinical Trials:
  • Collaborate with clinical researchers to design statistically sound clinical trials, determining sample sizes, randomization strategies, and statistical analysis plans. You’ll analyze trial data to assess drug efficacy, safety, and outcomes.
Perform Statistical Analysis for Research Studies:
  • Conduct complex statistical analyses for a range of medical and epidemiological studies. You’ll analyze data from observational studies, longitudinal research, and experimental trials, providing insights into trends, associations, and causal relationships.
Develop Statistical Models and Algorithms:
  • Build and refine statistical models that help understand and predict patient outcomes, disease progression, and treatment efficacy. You’ll work with big data, including patient registries, electronic health records, and genetic data, to develop predictive algorithms.
Collaborate on Regulatory Submissions:
  • Support the preparation of regulatory submissions, ensuring that statistical methodologies meet regulatory standards set by agencies like the FDA or EMA. You’ll provide statistical analysis results and interpretations for clinical study reports (CSRs) and regulatory filings.
Ensure Data Quality and Integrity:
  • Develop and implement data validation strategies to ensure the accuracy and reliability of data used in clinical trials and research studies. You’ll conduct data cleaning and manage missing data, ensuring that analyses are based on high-quality data.
Generate Reports and Visualizations:
  • Create detailed reports, data visualizations, and presentations that communicate the results of statistical analyses clearly to both technical and non-technical stakeholders. You’ll ensure that findings are presented in a way that supports decision-making in clinical research and healthcare.
Advise on Study Protocols and Statistical Best Practices:
  • Provide guidance to clinical research teams on statistical best practices, including study design, data collection methods, and appropriate statistical tests. You’ll ensure that research methodologies align with scientific and ethical standards.

Requirements

Required Skills:

  • Biostatistics and Data Analysis Expertise:Strong expertise in biostatistics, with experience applying statistical techniques to clinical trials, medical research, and epidemiological studies. You’re proficient in statistical software such as SAS, R, SPSS, or Python.
  • Clinical Trial Design and Analysis:Experience in designing and analyzing clinical trials, including sample size calculations, randomization techniques, and interim analysis. You know how to structure trials to ensure robust statistical outcomes.
  • Data Modeling and Statistical Methods:Expertise in developing statistical models and applying methods such as survival analysis, mixed-effects models, and Bayesian analysis. You’re familiar with handling longitudinal and multivariate data.
  • Regulatory Knowledge:Understanding of regulatory standards, including FDA and EMA guidelines, for statistical methodologies in clinical trials. You can prepare statistical analysis plans and provide inputs for regulatory submissions.
  • Communication and Collaboration:Excellent collaboration skills with the ability to work with multidisciplinary teams, including clinicians, researchers, and regulatory professionals. You can clearly communicate complex statistical concepts to non-experts.

Educational Requirements:

  • Master’s or Ph.D. in Biostatistics, Statistics, Epidemiology, or a related field.Equivalent experience in biostatistics applied to healthcare or clinical research is highly valued.
  • Certifications or additional coursework in clinical trial design, statistical programming, or healthcare data analysis are a plus.

Experience Requirements:

  • 3+ years of experience in biostatistics,with hands-on experience in analyzing clinical trial data or conducting medical research.
  • Experience working with statistical software such as SAS, R, SPSS, or Python for data analysis and model development.
  • Experience working in regulated environments and supporting regulatory submissions (e.g., FDA, EMA) is highly desirable.

Benefits

  • Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
  • Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
  • Work-Life Balance: Flexible work schedules and telecommuting options.
  • Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
  • Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
  • Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
  • Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
  • Tuition Reimbursement: Financial assistance for continuing education and professional development.
  • Community Engagement: Opportunities to participate in community service and volunteer activities.
  • Recognition Programs: Employee recognition programs to celebrate achievements and milestones.
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.