At a Glance
- Tasks: Lead data design and management for clinical studies, ensuring quality and integrity.
- Company: Join a pioneering biopharma company transforming healthcare with innovative technology.
- Benefits: Competitive salary, stock options, generous leave, wellness allowance, and learning opportunities.
- Other info: Dynamic startup culture with high agency and opportunities for professional growth.
- Why this job: Make a real impact in healthcare by improving clinical trial processes and patient outcomes.
- Qualifications: 5+ years in clinical data management; programming skills in Python, R, or SQL preferred.
The predicted salary is between 58500 - 71500 £ per year.
Our mission is to fix the broken clinical-stage biopharma model by building the next generation of biopharma through in-licensing clinical-stage therapeutic assets and developing them with Lindus Health’s integrated, technology-first clinical trial infrastructure.
The Data Architect owns assigned studies end-to-end, taking full responsibility for both the design of the database on Citrus and the quality of the data it produces, from study planning through database lock. The role designs with the final analysis in mind, writes code where manual review would slow delivery, and designs the edit checks and validation that prevent issues before they make their way downstream.
You have around 5+ years of experience across clinical data management and/or trial platform design, with hands-on involvement in study setup, data review, and database lock. You can design a study's data capture on an EDC platform and define its specification. You work with data programmatically, or are ready to build that skill quickly: Python, R, or SQL are used daily in this role.
You have working knowledge of CDISC standards, particularly CDASH, with SDTM familiarity a plus, and you design with analysis-ready data in mind. You understand GCP, ICH E6 and 21 CFR Part 11 and apply them in day-to-day decisions.
What you’ll focus on:
- Own your assigned studies end-to-end, from defining critical data items and the data management plan through to database lock.
- Own the design of your studies on Citrus, utilizing AI combined with your expert review to translate protocol requirements into a specification and edit check logic that captures clean, analysis-ready data.
- Assess feasibility and flag complexity and risk early, where a design choice could affect data integrity, participant safety or study endpoints.
- Manage the full query lifecycle from generation through resolution, working directly with sites.
- Lead proactive, risk-based data review, automated where possible, to keep key study milestones on track.
- Use scripting and AI tooling day-to-day to automate data review, flag anomalies, and surface issues earlier.
- Conduct all activities in line with relevant regulations and Lindus SOPs, keeping study documentation to a standard that holds up under audit or inspection.
What we offer (UK):
- Competitive salary, plus meaningful stock options.
- Flexible working: We encourage people to work 3 days per week from the office.
- 30 days annual leave in addition to Bank Holidays.
- £60 monthly wellness allowance.
- Enhanced Parental Leave: 16 weeks full pay for primary caregiver and 4 weeks full pay for secondary caregiver.
- £1,000 Learning and Development allowance each year.
- Regular whole company and team events, both in person and virtually.
- Access to gym and retail discounts through our benefits platform.
We believe hiring should be transparent, respectful of your time, and give you a real feel for what Lindus Health is like.
Data Architect in London employer: Lindus
Lindus Health is an exceptional employer, offering a unique opportunity to make a significant impact in the biopharma industry while working in a collaborative and innovative environment near London Bridge. With a strong focus on employee growth, we provide competitive salaries, generous annual leave, and a £1,000 annual learning allowance, alongside flexible working arrangements that promote work-life balance. Our commitment to wellness, enhanced parental leave, and regular team events fosters a supportive culture where every team member can thrive and contribute to our mission of transforming clinical trials.
StudySmarter Expert Advice🤫
We think this is how you could land Data Architect in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Lindus!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Architect at Lindus.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Lindus.
✨Apply Directly through Our Website
When you find a suitable opening like Data Architect at Lindus, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Architect in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Lindus, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Lindus. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Lindus
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Lindus!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
