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For Companies At a Glance
- Tasks: Transform complex scientific data into actionable insights and collaborate with scientists and engineers.
- 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 in scientific discovery and drive AI innovation.
- Qualifications: PhD or Masters with extensive experience in life sciences and data-driven solutions.
- Other info: Dynamic, collaborative environment with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
Who We Are
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 the last year alone, the world's dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships.
Who You Are
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 will need to be software-savvy and data fluent with skills to translate scientific workflow to data-related requirements and understand the software implication. 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 +5 years or Masters with +10 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 data-driven solutions in operational or productized environments that improved efficiency, reduced cost, and enhanced data utilization. Proven experience and capability to analyze and articulate the business impact of the data-driven solutions via ROI analysis, live presentation, case study.
- Exceptional communication and storytelling ability to engage technical and executive stakeholders.
- Extensive hands-on experience with scientific data workflows and lab automation; exposure to FAIR principles and modern data architecture is a plus.
- Prior experience in customer-facing, consulting, or commercial-scientific interface roles.
- Comfortable with basic scripting and data structures, and familiarity with software tools, databases.
What You Will Do
- Engage directly with customers onsite up to 4-5 days per week in the UK Region.
- 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 in Manchester employer: TetraScience
Contact Detail:
TetraScience Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Scientific Business Analyst in Manchester
✨Tip Number 1
Get to know TetraScience inside out! Familiarise yourself with the Tetra Way letter and think about how your values align with theirs. This will not only help you in interviews but also 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, and ask them about their experiences. This can give you insider knowledge and might even lead to a referral, which is always a bonus!
✨Tip Number 3
Prepare for those face-to-face interactions! Brush up on your communication skills and be ready to discuss how your background in life sciences can drive AI and machine learning applications. Show them you can bridge the gap between 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 in Manchester
Some tips for your application 🫡
Read the Tetra Way Letter: Before you dive into your application, make sure to read the Tetra Way letter from our CEO, Patrick Grady. It’s super important for understanding our values and whether we’re the right fit for each other. Reflect on it and let it guide your application!
Showcase Your Experience: When writing your application, highlight your experience in life sciences, especially in drug discovery or preclinical development. We want to see how your background aligns with our needs, so don’t hold back on those relevant skills and achievements!
Be Data-Driven: Since we’re all about scientific data and AI, make sure to include examples of how you’ve used data to drive decisions or improve processes. Show us your analytical mindset and how you 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 to the right people. Plus, it 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 reflect on the Tetra Way letter. This document is crucial for understanding the company's values and ethos. Aligning your answers with these principles will show that you’re a good cultural fit.
✨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 results in previous roles, especially in drug discovery or preclinical development.
✨Engage with Real-World Scenarios
Be ready to engage in discussions about real-world applications of AI and machine learning in life sciences. Think of innovative use cases you can propose based on your expertise, and be prepared to discuss how you would approach customer challenges.
✨Communicate Effectively
Practice your storytelling skills! You’ll need to convey complex ideas clearly to both technical and non-technical stakeholders. Prepare to explain your thought process and the business impact of your data-driven solutions in a way that resonates with diverse audiences.
