At a Glance
- Tasks: Lead the development of cheminformatics platforms and drive drug discovery decisions.
- Company: Join a venture-backed biotech in London focused on innovative oncology therapies.
- Benefits: Enjoy a hands-on leadership role with opportunities for growth and influence.
- Why this job: Shape strategy while collaborating with top scientists in a cutting-edge environment.
- Qualifications: PhD in cheminformatics or related field; strong coding and leadership skills required.
- Other info: Be part of a dynamic team transforming cancer treatment through data-driven discovery.
The predicted salary is between 72000 - 108000 £ per year.
VP of Cheminformatics
My client is a venture-backed biotech in London developing small-molecule therapies for oncology. Backed by top-tier investors and led by proven drug developers, they’re combining cutting-edge cancer biology with data-driven discovery to build a new kind of pipeline.
The VP of Cheminformatics will know how to build smart, scalable informatics platforms and drive real-world decisions in drug discovery. This is a hands-on leadership role. You’ll sit across chemistry, biology and data science, working closely with the C-suite and other functional heads. You’ll have the freedom to shape strategy and team structure, but will also be expected to roll your sleeves up and contribute technically.
Key Responsibilities:
- Build and own the company’s cheminformatics infrastructure from core tools to broader platform strategy
- Develop and deploy pipelines that integrate screening data, SAR, predictive models and structural insights
- Drive informatics strategy across multiple drug discovery programmes, from early hit-finding through to candidate nomination
- Collaborate daily with medicinal chemists, biologists and data scientists to improve compound design and prioritisation
- Lead the selection and implementation of third-party tools, vendors and data systems
- Hire, mentor and lead a small (but growing) informatics team
- Act as a core member of the scientific leadership team, contributing to broader R&D strategy
Experience Required:
- Substantial experience in cheminformatics roles at biotech or pharma ideally with direct exposure to oncology programmes
- Proven ability to build and implement cheminformatics tools used in active drug discovery
- Strong technical grounding
- Comfortable coding in Python and working with structural and screening datasets
- Familiarity with ML/AI platforms for drug design
- Strong leadership skills able to influence cross-functionally and build out high-performing teams
- PhD (or equivalent) in cheminformatics, computational chemistry or related field preferred
Vice President of Cheminformatics employer: Nexia
Contact Detail:
Nexia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Vice President of Cheminformatics
✨Tip Number 1
Network with professionals in the biotech and cheminformatics fields. Attend industry conferences, webinars, or local meetups to connect with potential colleagues and leaders in the sector. This can help you gain insights into the company culture and the specific challenges they face.
✨Tip Number 2
Showcase your technical skills by engaging in relevant projects or contributing to open-source cheminformatics tools. This not only demonstrates your expertise but also highlights your commitment to the field, making you a more attractive candidate.
✨Tip Number 3
Prepare to discuss your leadership style and experiences in building teams. Be ready to share specific examples of how you've successfully led cross-functional collaborations, as this role requires strong influence across various departments.
✨Tip Number 4
Familiarise yourself with the latest trends in cheminformatics and drug discovery, particularly in oncology. Being knowledgeable about current advancements and challenges will allow you to engage in meaningful conversations during interviews and demonstrate your passion for the role.
We think you need these skills to ace Vice President of Cheminformatics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in cheminformatics, particularly in biotech or pharma settings. Emphasise your technical skills, especially in Python and any familiarity with ML/AI platforms for drug design.
Craft a Compelling Cover Letter: In your cover letter, express your passion for oncology and how your background aligns with the company's mission. Mention specific achievements in building cheminformatics tools and leading teams, showcasing your leadership skills.
Showcase Technical Expertise: Include examples of projects where you developed and deployed cheminformatics pipelines. Highlight your ability to integrate screening data and predictive models, demonstrating your hands-on experience in drug discovery.
Highlight Collaborative Experience: Discuss your experience working cross-functionally with medicinal chemists, biologists, and data scientists. Illustrate how you've contributed to R&D strategy and improved compound design through collaboration.
How to prepare for a job interview at Nexia
✨Showcase Your Technical Expertise
As a VP of Cheminformatics, it's crucial to demonstrate your technical grounding. Be prepared to discuss specific cheminformatics tools you've built or implemented, especially those used in drug discovery. Highlight your coding skills in Python and any experience with ML/AI platforms.
✨Emphasise Leadership Experience
This role requires strong leadership skills, so be ready to share examples of how you've successfully led teams in the past. Discuss your approach to mentoring and building high-performing teams, and how you’ve influenced cross-functional collaboration.
✨Align with Company Goals
Research the company's mission and current projects in oncology. During the interview, align your experience and vision with their goals, particularly how you can contribute to their drug discovery pipeline and informatics strategy.
✨Prepare for Technical Questions
Expect to face technical questions related to cheminformatics, data integration, and predictive modelling. Brush up on relevant concepts and be ready to discuss how you've applied them in real-world scenarios, particularly in relation to candidate nomination and hit-finding.