Senior Manager, Data Integrity Quality Assurance

Astellas Pharma Inc.
united kingdom
2 weeks ago
Create job alert

DescriptionSenior Manager, Data Integrity Quality AssuranceAbout Astellas: At Astellas we are a progressive health partner, delivering value and outcomes where needed. We pursue innovative science, focussing 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 care-givers, to ensure 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: In this role, you will be responsible for directing the Data Integrity governance activities applicable to GMP/GDP globally. You will serve as the Data Integrity Officer for GMP/GDP areas, providing management and strategic leadership to develop and manage the Data Governance Program. Additionally, you will contribute to the development, implementation, and successful execution of the QA mission, objectives, and long-term strategic plan. Hybrid Working: At Astellas we recognize that our employees enjoy having balance between their professional and home lives. We are proud of our hybrid approach which empowers you to have flexibility on whether to work from home or in the office. Key Activities for this role:

Executing the DIQA compliance oversight program, ensuring issue resolution, audits, and regulatory inspection preparation. Providing regulatory intelligence and interpret requirements to support global process improvement initiatives. Developing and implementing quality strategies for Data Integrity compliance and technology solutions, leading initiatives across multiple departments. Supporting the DIQA internal and vendor audit program, ensuring compliance assessments, audits, and corrective actions. Collaborating with business functions to lead continuous process improvements in data integrity and regulatory compliance.

Essential Knowledge & Experience: Substantial pharmaceutical industry experience paired with Quality Assurance expertise. Effective communication, writing, and interpersonal skills for interfacing across departments and with external stakeholders. Detailed knowledge of GXP regulations, computerized systems in GXP environments, and quality principles. Expertise in global industry standards and regulatory requirements for software development, computer system validation, data integrity, and Electronic Records/Signatures. Ability to interact with regulatory agencies globally and develop effective relationships with internal and external stakeholders. Preferred Qualifications: Problem-solving skills to define business needs, identify possible solutions, and develop executable plans with available resources. Capability to work effectively in culturally diverse situations. Application of processes, methods, skills, knowledge, and experience to achieve specific project objectives within agreed parameters, timescales, and budgets. Ability to document processes in straightforward, easy-to-understand explanations and instructions within a QA subject. Education/Qualifications: A bachelor's degree or equivalent experience is required. Fluency in English is essential for effective communication with global stakeholders. Additional Information: This is a permanent, full-time position. This position is based in London, UK This position follows our hybrid working model. The role requires a blend of home and approx. 1 day per quarter in our London 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, colour, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. #LI-Addlestone#LI-Hybrid

Related Jobs

View all jobs

IT Project Manager

Digital Operations Manager, IT Manager, IT Support Manager

Head of Internal Audit

Data Architect

Systems Accounting Manager

Purchasing Manager

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.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.