Data Scientist - Real world data - FSP

THE COMPANY

Phastar is a multiple award-winning global biometric Contract Research Organization (CRO) that is accredited as an outstanding company to work for by Best Companies. We partner with pharmaceutical, biotechnology and medical device organizations to provide the expertise and processes to manage and deliver on time, quality biostatistics, programming, data management and data science services. With offices across the UK, US, Germany, Denmark, Kenya, Australia, India, China and Japan, Phastar is the second largest specialized biometrics provider globally, and the largest in the UK.

Our unique approach to data analysis, “The Phastar Discipline”, has led us to build a reputation for outstanding quality. With this as our core focus, we’re looking for talented individuals who share our passion for quality and technical expertise to join our team.

WHY PHASTAR

Accredited as an outstanding company to work for, Phastar is committed to employee engagement, workplace satisfaction and ensuring a healthy work-life balance. We offer flexible working, part-time hours, involvement in developing company-wide initiatives, structured training and development plans, and a truly supportive, fun and friendly environment.

What’s more, when you join our team, Phastar will plant a tree in your honour, as one of our Environmental, Social and Governance (ESG) initiatives. So, not only would you get your dream job, you’ll also be helping to save the planet!

THE ROLE

We are seeking a Senior Data Scientist within our FSP team, to work embedded within the sponsor project team. Within this role you will work with R programming language, R Shiny and Python on clinical and non-clinical trials to product complex datasets and outputs.

This will be a diverse role that will involve; the creation of R shiny Apps, conversion of R to SAS and Visa-Versa, creating complex macros, reviewing and updating complex data specifications and understanding Statistical Analysis Plans (SAPs).

This position is remote, although it can be office based or hybrid, depending on your location.

Responsibilities

• Develop and maintain advanced R Shiny applications to visualize and interact with complex datasets
• Perform statistical analysis and predictive modeling using R, SAS, Python, and other statistical software, ensuring the integrity and accuracy of analyses
• Work closely with clinical teams to understand data requirements and implement solutions that adhere to clinical data standards (e.g., CDISC, ADaM)
• Research and implement cutting-edge machine learning/deep learning/artificial intelligence techniques to enhance data analysis efficiency and effectiveness
• Collaborate with cross-functional teams to design and execute data-driven strategies that support drug discovery and development processes
• Ensure compliance with industry standards and regulatory requirements related to data management and analysis
• Stay abreast of latest trends, technologies, and methodologies in data science, machine learning, and biotech/pharma industries to continually improve our analytics capabilities
• Collaborate closely with biostatisticians, data managers, and other stakeholders to understand project requirements and deliver timely results
• Present findings and provide technical support to internal teams and external partners
• Maintain thorough documentation of all programming activities to ensure reproducibility and adherence to internal standards
• Conduct rigorous quality control checks on all deliverables to ensure accuracy and compliance with regulatory standards

Qualifications

• Advanced degree (MSc or PhD) in Data Science, Statistics, Computer Science, Bioinformatics, or a related field
• Proven fluency in multiple programming languages and statistical analysis tools, including R, SAS, and Python. Expertise in creating advanced R Shiny applications is a must
• Demonstrated experience in analyzing clinical trial data and a thorough understanding of clinical data standards (CDISC, ADaM, etc.)
• Knowledge in machine learning, deep learning, and artificial intelligence, with a track record of implementing new techniques and tools to improve data analysis processes
• Excellent problem-solving abilities and a strong commitment to quality
• Ability to work collaboratively in a fast-paced, interdisciplinary environment
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders