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MMS

Study Design Statistician (Remote)

canton charter township, MI

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About this opportunity

MMS lists this Study Design Statistician (Remote) opportunity in canton charter township, Michigan. Review the employer’s description below for duties, qualifications and application requirements.

Job description

Are you looking to join a company where your contributions truly matter, and where you'll be part of a supportive, innovative team? MMS is a award-winning, data-focused clinical research organization (CRO). We pride ourselves on being a Great Place to Work certified organization, recognized for our exceptional culture and industry best employee retention rate. We support the pharmaceutical, biotech, and medical device industries with our proven, scientific approach to complex trial data and regulatory submission challenges. With a global footprint across four continents, MMS not only maintains an industry-leading customer satisfaction rating but also fosters a collaborative and inclusive work environment where employees can thrive. Join us at MMS and be part of a team that is shaping the future of clinical research.

Discover more about our exciting opportunities and why MMS is a great place to advance your career. Visit or follow MMS on LinkedIn.

As part of our Strategic Statistical Services Arm, this is a full-time role with emphasis on being an internal and external SME for clinical trial design, together with providing consultation to advise clients on a range of broader statistical issues, and will have an internal job title of Strategic Statistician.

Job Description:

Our experienced statisticians and programmers develop intellectual property and assets to support the design and analysis of clinical trials, precision medicine and real-world data analytics. We address the emerging analytics needs of the Industry with our biostatistics services, bespoke algorithms and unique, state of the art, proprietary, cloud-based trial simulation software KerusCloud. Working alongside innovative statisticians you will be responsible for leading the full life-cycle of KerusCloud support and statistical services, from:

Assisting customers with their study design with a particular focus on simulation with KerusCloud to ensure they are aligned with the study objectives

Preparation of study protocols and development of Statistical Analysis Plans and Statistical Analysis Reports

Summarize, analyze and visualize study data using a variety of statistical methods, ultimately delivering results to an agreed timeline with optimal quality

Provide statistical consultancy support to sponsors across the full span of clinical development, including oversight of third-party statistical and programming deliverables

Maintain current knowledge of relevant research techniques such as modelling, simulation and experimental design and participate in continuous professional development activity

Support pre-sales discussions to understand and identify client needs, then contribute to technical solutions and resource/ cost estimates

Collaborate with the Product Development team defining key features and statistical aspects of KerusCloud

Provide input and support to Marketing of KerusCloud, including demonstrations to clients, white papers, etc

Requirements:

Bachelors degree in mathematics, statistics, physics, pharmacology or with a strong statistical component, Masters or PhD preferred

5-7 years of experience in the application of medical statistics (pharma, CRO, academic)

Willingness to engage with clients to understand and research problems and provide creative, business-orientated solutions

Experience in delivering customer projects to high quality standards

Experience in SAS and/ or R statistical software packages

Experience in study design and protocol and report-writing preferred

Experience of modelling and simulation techniques to explore complex study designs preferred

Experience of Bayesian approaches to design and analysis of clinical data preferred

Experience of early-phase drug development processes including innovative/ adaptive study design preferred.

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