Head, Medical Affairs Statistical Science

Astellas Europe
1 week ago
Create job alert

Head, Medical Affairs Statistical Science

About Astellas:

At Astellas we are a progressive health partner, delivering value and outcomes where needed. We pursue innovative science, focusing initially on the areas of greatest potential and then developing solutions where patient need is high, often in rare or under-served disease areas and in life-threatening or life-limiting diseases and conditions.

We work directly with patients, doctors, and health care professionals on the front line to ensure patient and clinical needs are guiding our development activities at every stage. Our global vision for Patient Centricity is to support the development of innovative health solutions through a deep understanding of the patient experience. At Astellas, Patient Centricity isn’t a buzzword - it’s a guiding principle for action. We believe all staff have a role to play in creating a patient-centric culture and integrating an awareness of the patient into our everyday working practices, regardless of our role, team, or division.

We work closely with regulatory authorities and payers to find new ways to ensure access to new therapies. We deliver the latest insights and real-world evidence to inform the best decisions for patients and their caregivers, ensuring the medicines we develop continue to provide meaningful outcomes. Beyond medicines, we support our stakeholder communities to drive initiatives that improve awareness, education, access, and ultimately standards of care.

The Opportunity:

As a Head, Statistical Science, you should have previous experience as a line manager and exceptional knowledge of the scientific area of responsibility. The position will require experience in complex and not well-understood statistical topics and/or disease states and/or RWD Science, as well as the ability to lead change and learn quickly technical topics.

You are also expected to consistently and significantly impact the technical capabilities of the department and the external scientific community. You will be responsible for supporting the key company priorities: BOLD, Growth Strategy and Sustainable Margin Transformation (SMT), which includes development and maintenance of excellence in portfolio, product and study design, optimal use of Real-World Data to support Medical Affairs tactics, and development, analysis and reporting standards, and innovative methodologies use.

You will work independently and involve the right level of participants as needed (cross-functional peers, Sr management, Primary Focus Statistics Lead (PFSL)) within or outside M&D. The position represents Astellas in interfaces with regulatory agencies globally, chairs sessions in international statistics meetings, participates in industry-wide technical discussions, and represents Astellas in professional societies.

Hybrid Working:

At Astellas, we recognize the importance of balancing your work and home life, so we offer a hybrid working solution allowing time to connect with colleagues in person at the office alongside the flexibility to work from home; optimizing the most productive work environment for you to succeed and deliver.

Key Activities for this role:

  • The position directs Astellas statistical strategy, creates and organizes new areas of methodological research, and is accountable to provide best-in-class data science support to Astellas drug development programs.
  • Advises project teams and statistical leads on challenging statistical design, analysis, and decision-making issues.
  • Performs/supervises modeling and simulations, leverages external experts to provide input to clinical development issues, and participates in due diligence activities, reviews data, and advises the company.
  • Presents and defends complex statistical solutions to internal governance committees, key stakeholders, or regulatory bodies in a compelling and impactful way.
  • Institutes best practices regarding planning, execution, interpretation, publication, communication, and regulatory/HTA submission of assets - Writes statistical position papers.
  • Challenges and influences peers and senior managers inside and outside of Data Science on best practices in their area of competence.
  • Coaches and supports statistical leads in providing best-in-class data science support to Astellas drug development programs.

Essential Knowledge & Experience:

  • Substantial years of experience in applying statistical methods in biomedical research, Pharma, CRO, Academia, or Healthcare industry or in providing statistical direction in these areas.
  • Understanding of pharmaceutical industry leading practices (e.g., regulatory framework, inspection process, HTA guidance, technologies, systems, etc.).
  • Advanced and broad knowledge of statistical methods, along with understanding of industry practices related to the statistical analysis of clinical data.
  • Knowledge and skills in SAS required, knowledge of R preferred.
  • Record of publications in clinical trials or methodological research in highly regarded peer review journals or invited speaking engagements.
  • Understand Real World Evidence, omics, digital endpoints, and Machine Learning.

Education/Qualifications:

  • PhD or M.S. in Biostatistics, Statistics, or related scientific field.

Additional information:

  • This is a permanent position in the United Kingdom or Canada.
  • Role requires a blend of home and minimum once a quarter in our Regional or Affiliate Astellas office. Flexibility may be required in line with business needs.
  • Candidates must be located within a commutable distance of the office.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

#J-18808-Ljbffr

Related Jobs

View all jobs

Engineering Scientist

Head of Data - Leeds - Hybrid Remote - £110k - £140k

Head of Data Architecture

Head of Data Architecture

Head of Data Architecture

Head of Software Engineering

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.