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For Companies At a Glance
- Tasks: Optimise virtual screening and lead interdisciplinary projects in drug discovery.
- Company: AQEMIA, a pioneering drug invention company transforming medicine.
- Benefits: Competitive salary, flexible work arrangements, and collaboration with top talent.
- Why this job: Make a real impact on drug discovery and tackle complex scientific challenges.
- Qualifications: PhD with 8+ years in Data Science or related fields and strong Python skills.
- Other info: Join a world-class team at the forefront of AI and life sciences.
The predicted salary is between 43200 - 72000 £ per year.
Overview
AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. At the core of our mission is QEMI, our proprietary molecule-invention platform, which uniquely combines cutting-edge science with advanced technology. Powered by physics-based modeling, statistical mechanics, and generative AI, QEMI allows our teams to design novel drug candidates from first principles.
What makes AQEMIA different is our commitment to true innovation: our research is dedicated to the invention of new molecular entities, not the refinement of existing ones. We focus on inventing never-before-seen molecules, without relying on experimental data, and advancing them into a growing pipeline of proprietary programs and strategic partnerships with leading pharmaceutical companies. Our most advanced preclinical programs are currently in vivo optimization, targeting diseases still waiting for effective treatments, offering our teams the opportunity to work on science that can make a real difference in people’s lives.
The Role
- You will join the Rocket Launcher team, which is dedicated to hit identification.
- Your role is to optimise virtual screening and hit optimisation pipelines using a multidisciplinary approach.
- You’ll collaborate across scientific domains and lead cross-functional projects to integrate cutting-edge computational technologies.
- Evaluate and test virtual screening and hit optimisation pipelines for scientific effectiveness.
- Align computational strategies with team objectives and drug discovery goals.
- Lead interdisciplinary projects across physics, chemistry, data science, and ML teams.
- Apply in-depth statistical (bayesian optimisation) and exploratory data analyses to improve pipeline performance.
- Identify technical gaps and develop custom solutions.
- Contribute to best practices in data analysis, coding, and screening workflows.
- Stay current on literature and recommend improvements in virtual screening and hit optimisation.
- Advise stakeholders on the technical feasibility and impact of proposed approaches.
- Actively participate in planning analyses and identifying priorities and dependencies.
What we’re looking for
- PhD or equivalent with 8+ years in Data Science, Physics, Computational Chemistry, or related fields.
- Strong Python programming skills.
- Deep experience in scientific data analysis, ideally in life sciences.
- Solid understanding of statistical methods, bayesian optimisation and exploratory data analysis.
- Demonstrated experience leading multi-team scientific initiatives.
Nice-to-Have:
- Familiarity with tools like RDKit, OpenMM, or SMILES or experience with molecular simulation data.
- Knowledge of high-performance computing or cloud environments.
Preferred Mindset
- Pragmatic and Impact-Driven - Focused on delivering solutions that work in real-world applications, balancing scientific rigor with practical usability.
- Eagerness to Learn - A strong curiosity for scientific advancements and a willingness to continuously expand your expertise.
- Love for High Scientific Challenges - Enthusiasm for tackling complex problems at the frontier of AI and drug discovery.
- Team-Oriented - A collaborative spirit, thriving in an interdisciplinary environment.
- Humility - Open to feedback and different perspectives, always striving for improvement.
Polite note: UK visa sponsorship not currently available for this role at this time.
Why Join Us?
- At AQEMIA, we work for a mission: joining us means having your own impact on changing the way drugs are discovered, and helping to shape the direction of our fast-growing company and team.
- Expanding Drug Discovery Pipeline: Focused on critical therapeutic areas like Oncology, CNS, Immuno-inflammation... with in vivo proof of concept/patent stage programs. Collaborations with top Pharma, including a $140M Sanofi deal.
- World-Class Interdisciplinary Team: work alongside exceptional talent at the intersection of technology and life sciences. Our teams combine deep expertise in AI, physics-based modeling, biology, and medicinal chemistry to push the boundaries of innovation.
- DeepTech Recognition: AQEMIA is proud to be part of the French Tech 120 and France 2030, highlighting our role as a key player in Europe’s DeepTech ecosystem.
- Prime Location with Flexibility: Our offices are located in the heart of Paris and London (King’s Cross), with flexible work arrangements including up to two remote days per week.
- Strong Financial Backing: $100M raised from leading European and International investors.
Senior/Staff Data Scientist employer: Aqemia
Contact Detail:
Aqemia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior/Staff Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at AQEMIA. Use LinkedIn to connect and engage with their posts. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Prepare for interviews by diving deep into AQEMIA's work. Familiarise yourself with their QEMI platform and recent projects. Show them you’re not just another candidate; you’re genuinely interested in their mission and how you can contribute.
✨Tip Number 3
Practice your technical skills! Brush up on Python and statistical methods relevant to the role. Be ready to discuss your past projects and how they align with AQEMIA’s focus on innovative drug discovery.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the AQEMIA team.
We think you need these skills to ace Senior/Staff Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the specific skills and experiences that align with the Senior/Staff Data Scientist role. Highlight your Python programming skills and any relevant experience in scientific data analysis, especially in life sciences.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about drug discovery and how your background makes you a great fit for AQEMIA. Be sure to mention your eagerness to learn and tackle high scientific challenges.
Showcase Your Team Spirit: Since we value collaboration, share examples of how you've successfully led interdisciplinary projects or worked within teams. This will help us see your team-oriented mindset in action!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows your enthusiasm for joining AQEMIA!
How to prepare for a job interview at Aqemia
✨Know Your Science
Make sure you brush up on the latest advancements in drug discovery, especially around computational chemistry and data science. Be ready to discuss how your experience aligns with AQEMIA's mission of inventing new molecular entities and how you can contribute to their innovative approach.
✨Showcase Your Technical Skills
Prepare to demonstrate your Python programming skills and your understanding of statistical methods like Bayesian optimisation. You might be asked to solve a problem or analyse data on the spot, so practice coding challenges and be ready to explain your thought process clearly.
✨Highlight Collaboration Experience
Since the role involves leading interdisciplinary projects, be prepared to share examples of how you've successfully collaborated across different scientific domains. Discuss specific projects where you integrated various technologies and how you navigated any challenges that arose.
✨Emphasise Your Pragmatic Mindset
AQEMIA values a pragmatic and impact-driven approach, so be ready to talk about how you've balanced scientific rigor with practical usability in your past work. Share instances where your solutions made a real-world impact, and express your eagerness to tackle high scientific challenges.
