At a Glance
- Tasks: Join a dynamic team to analyse data and drive drug design analytics.
- Company: Innovative drug discovery company focused on cutting-edge technology.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Make a real impact in healthcare by optimising drug design processes.
- Qualifications: Strong background in statistics, coding skills in Python and SQL, and data analysis experience.
The predicted salary is between 50000 - 70000 £ per year.
Requirements
- Strong background in statistics and data analysis
- Strong coding skills in Python and SQL including experience using data science toolkits such as NumPy, SciPy, or Pandas
- Proven experience in a data science or platform analytics role ideally in a drug discovery company
- Experience defining and measuring metrics for engineering or product performance (e.g., efficiency, bottlenecks, KPIs)
- Familiarity with the early drug discovery process
- Ability to communicate complex data insights to a diverse range of stakeholders, including engineers and scientists
- (Desirable) Familiarity with data engineering concepts and experience with running jobs on Cloud-based infrastructure
What the job involves
This is an exciting opportunity to join the data team at IsoLabs. You will work alongside Data Curators, Engineers, AI experts, and Drug Discovery scientists to drive the analytics that underpin our drug design engine. As a Data Scientist focused on platform analytics, you will be responsible for capturing and analysing data to understand how our technology and drug design processes are performing. You will provide the robust data science expertise needed to turn business intelligence into actionable insights, helping Product, Data, Engineering, Research, and Drug Discovery teams make the best possible decisions to accelerate the delivery of new medicines.
- Analyze business intelligence data to provide robust and insightful outputs that drive decision-making across product, engineering, and research teams
- Partner with the Engineering, Product, and drug discovery teams to implement telemetry and traceability, ensuring we capture drug design intent and metadata effectively
- Design and track key metrics (KPIs) to evaluate if we are building the most efficient drug design engine and progressing towards our long-term goals
- Conduct internal and external benchmarking on Machine Learning model performance and drug discovery processes
- Identify bottlenecks in the end-to-end delivery system to optimize real-world delivery
- Collaborate with engineering to build an analytics layer that supports generalizable drug design and helps determine the impact of our models on success rates
Data Scientist (Analytics) employer: Isomorphic Labs
IsoLabs is an exceptional employer that fosters a collaborative and innovative work culture, where Data Scientists can thrive alongside experts in engineering, AI, and drug discovery. With a strong emphasis on employee growth, we offer opportunities for professional development and the chance to make a meaningful impact in the field of drug design. Located in a vibrant area, our team enjoys a supportive environment that values diverse perspectives and encourages the sharing of complex data insights.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist (Analytics)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at IsoLabs or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data analysis projects, especially those using Python and SQL. This will help you demonstrate your coding chops and make you stand out during interviews.
✨Tip Number 3
Practice your communication skills! Be ready to explain complex data insights in simple terms. You’ll need to connect with engineers and scientists, so being able to bridge that gap is key.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at IsoLabs.
We think you need these skills to ace Data Scientist (Analytics)
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your strong background in statistics and data analysis. We want to see your coding skills in Python and SQL shine through, so don’t hold back on showcasing your experience with data science toolkits like NumPy, SciPy, or Pandas.
Tailor Your Application:When applying, tailor your application to reflect the specific requirements of the Data Scientist role. Mention any relevant experience in a drug discovery company and how you’ve defined and measured metrics for engineering or product performance.
Communicate Clearly:We value the ability to communicate complex data insights effectively. In your application, give examples of how you've shared insights with diverse stakeholders, including engineers and scientists, to demonstrate your communication skills.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our data team at IsoLabs.
How to prepare for a job interview at Isomorphic Labs
✨Brush Up on Your Stats and Coding Skills
Make sure you're comfortable discussing statistics and data analysis, as well as your coding skills in Python and SQL. Be ready to share specific examples of how you've used tools like NumPy, SciPy, or Pandas in your previous roles.
✨Know the Drug Discovery Process
Familiarise yourself with the early drug discovery process. Understanding this will help you connect your analytics work to the broader goals of the company, showing that you can contribute meaningfully to their mission.
✨Prepare to Communicate Insights
Practice explaining complex data insights in simple terms. You might be asked to present findings to engineers and scientists, so being able to communicate effectively with diverse stakeholders is key.
✨Think About Metrics and Performance
Be prepared to discuss how you've defined and measured metrics in past projects. Think about examples where you've identified bottlenecks or optimised processes, as this will demonstrate your analytical mindset and problem-solving skills.
