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- Tasks: Explore customer data and develop innovative AI/ML use cases in life sciences.
- Company: Join TetraScience, a leader in scientific data and AI revolution.
- Benefits: Competitive salary, equity, generous PTO, and remote work options.
- Why this job: Make a real impact by bridging science and technology in a dynamic environment.
- Qualifications: PhD with 15+ years in life sciences and strong coding skills.
- Other info: Collaborative culture focused on continuous improvement and scientific transformation.
The predicted salary is between 36000 - 60000 £ per year.
TetraScience is the Scientific Data and AI company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next gen lab data management solutions, scientific use cases, and AI-enabled outcomes. TetraScience is the category leader in this vital new market, generating more revenue than all other companies in the aggregate.
In connection with your candidacy, you will be asked to carefully review the Tetra Way letter, authored directly by Patrick Grady, our co-founder and CEO. This letter is designed to assist you in better understanding whether TetraScience is the right fit for you from a values and ethos perspective. It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day.
You are a strategic, analytically minded professional with a passion for bridging scientific insights and cutting-edge technology. You thrive in environments where you can collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes. With deep domain knowledge in drug discovery/preclinical development, CMC, or Quality, you are skilled at uncovering innovative use cases that drive AI and machine learning applications. Your ability to engage with scientists and business leaders alike makes you a key player in maximizing the value of scientific data.
You will need to be a high clock speed and forward-thinking individual with a passion for developing requirements for complex solutions targeted to R&D and Quality personas inside of Life Sciences. You embody extreme ownership and have a demonstrated history of deriving maximum value from data through enrichment, analysis, and integration with AI and machine learning applications. You should also be energized by regularly working onsite with customers. You thrive in dynamic, high-impact, face-to-face collaborative environments where you can build deep relationships and drive scientific transformation firsthand.
Requirements
- PhD with 15+ years of industry experience in life sciences, preferably across pharma, biotech, or health tech, with deep domain expertise in discovery, preclinical, CMC, and/or Quality.
- Extensive hands-on experience or direct oversight in one or more of the following areas: high throughput screening, preclinical toxicology, materials engineering, analytical development, drug substance (DS) synthesis and manufacturing.
- Delivered requirements for AI/ML-driven solutions in operational or productized environments that improved efficiency, reduced cost, and enhanced data utilization.
- Extensive hands-on experience with scientific data workflows and lab automation; exposure to FAIR principles and modern data architecture is a plus.
- Strong coding or scripting background (e.g., Python, Nextflow, AWS, SDKs) and familiarity with scientific tools, databases, and ontologies is preferred.
- Exceptional communication and storytelling ability to engage technical and executive stakeholders.
- Prior experience in customer-facing, consulting, or commercial-scientific interface roles.
What You Will Do
- Customer Data Exploration: Investigate diverse customer datasets, identifying enrichment and AI-readiness opportunities.
- Scientific Use Case Development: Collaborate with customers to define, iterate, and implement innovative scientific AI/ML use cases.
- Stakeholder Engagement: Conduct onsite interviews and workshops to deeply understand customer challenges and data landscapes.
- Data Analysis and Enrichment: Perform exploratory data analysis and define transformation workflows that enable scientific AI.
- Workflow Documentation: Develop visual documentation including workflow diagrams, ERDs, and ontology definitions.
- AI Model Evaluation: Provide practical scientific input on model output, with suggestions to improve real-world performance.
- Customer Enablement: Deliver onsite demonstrations, conduct working sessions, and act as a trusted advisor in AI adoption.
- Strategic Insight: Propose new directions, experiments, or platforms that can amplify scientific discovery and development.
Benefits
- Competitive Salary and equity in a fast-growing company.
- Supportive, team-oriented culture of continuous improvement.
- Generous paid time off (PTO).
- Remote working opportunities, when not at customer sites.
Scientific Business Analyst - United Kingdom employer: TetraScience
Contact Detail:
TetraScience Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Scientific Business Analyst - United Kingdom
✨Tip Number 1
Get to know TetraScience inside out! Dive into their mission and values, especially the Tetra Way letter. This will help you align your answers during interviews and show that you're genuinely interested in being part of their team.
✨Tip Number 2
Network like a pro! Reach out to current or former employees on LinkedIn. Ask them about their experiences and any tips they might have for standing out in the application process. Plus, it shows initiative!
✨Tip Number 3
Prepare for those face-to-face interactions! Brush up on your storytelling skills to effectively communicate your past experiences and how they relate to the role. Remember, they want to see how you can bridge science and tech.
✨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 TetraScience family.
We think you need these skills to ace Scientific Business Analyst - United Kingdom
Some tips for your application 🫡
Know the Tetra Way: Before you dive into your application, make sure to read the Tetra Way letter from our CEO, Patrick Grady. It’s a key document that’ll help you understand our values and whether you’re a good fit for us.
Tailor Your CV: When crafting your CV, highlight your experience in life sciences and any relevant projects you've worked on. We want to see how your background aligns with our mission of transforming scientific data into actionable insights.
Showcase Your Skills: Don’t forget to mention your coding or scripting skills! If you’ve got experience with Python or AI/ML solutions, let us know. We love seeing how candidates can bridge the gap between science and technology.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at TetraScience
✨Know the Tetra Way
Before your interview, make sure to read and understand the Tetra Way letter. This document is crucial for aligning with the company's values and ethos. Reflect on how your own values match up with theirs, as this will be a key topic during your discussion.
✨Showcase Your Analytical Skills
Prepare to discuss specific examples from your past experience where you've successfully transformed complex scientific data into actionable insights. Highlight your analytical mindset and how it has driven AI and machine learning applications in your previous roles.
✨Engage with Real-World Scenarios
Be ready to engage in discussions about real-world challenges faced by customers in the life sciences sector. Think of innovative use cases you could propose that leverage AI/ML solutions, demonstrating your ability to bridge the gap between science and technology.
✨Communicate Effectively
Practice your storytelling skills to ensure you can clearly communicate technical concepts to both scientific and business stakeholders. Use examples that showcase your exceptional communication abilities, as this will be vital in building relationships and driving scientific transformation.
