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For Companies At a Glance
- Tasks: Join a dynamic team to analyse data and drive cancer drug discovery.
- Company: SoCode is a leading biotech firm focused on innovative cancer therapies.
- Benefits: Enjoy flexible working options and opportunities for professional growth.
- Why this job: Make a real impact in healthcare while collaborating with top scientists.
- Qualifications: PhD or MSc in data science or related field; programming skills required.
- Other info: Located in vibrant Cambridge, this role offers a chance to innovate in biotech.
The predicted salary is between 28800 - 48000 £ per year.
The candidate should meet the following requirements:
Role Description
The ideal candidate will have experience as a Data Scientist in the biotech sector, focusing on drug discovery, with a passion for developing computational methods to advance cancer therapies.
Key Responsibilities:
- Collaborate with cross-functional teams including biologists, chemists, and computational scientists to drive oncology drug discovery through data-driven insights.
- Apply advanced statistical, machine learning, and computational techniques to analyze large-scale multi-omics, genomic, and clinical datasets, accelerating the identification of novel cancer targets and biomarkers.
- Develop and optimize predictive models to identify therapeutic response patterns and enhance patient stratification for cancer clinical trials.
- Build and implement scalable data pipelines and workflows for high-throughput drug screening and mechanistic studies.
- Integrate internal and external datasets to generate actionable insights into cancer biology, drug mechanisms, and disease progression.
- Present findings and data-driven insights to stakeholders, influencing drug development strategies.
- Stay at the forefront of advancements in data science, machine learning, and computational biology to continuously bring innovation to the team.
Key Qualifications:
- PhD, MSc, or equivalent experience in data science, bioinformatics, computational biology, or a related field.
- Proven experience applying data science and machine learning to biological or clinical datasets, ideally within oncology or drug discovery.
- Proficiency in programming languages such as Python, R, and experience with data analysis libraries (e.g., TensorFlow, scikit-learn).
- Strong understanding of statistical modeling, machine learning algorithms, and multi-omics data analysis (e.g., genomics, transcriptomics, proteomics).
- Experience working with large-scale biological databases and integrating multi-modal datasets.
- Excellent problem-solving skills and ability to work both independently and in a team-oriented environment.
- Strong communication skills, with the ability to present complex data findings to both scientific and non-scientific audiences.
Data Scientist | Cambridge | Biotech (Drug Discovery) employer: SoCode
Contact Detail:
SoCode Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist | Cambridge | Biotech (Drug Discovery)
✨Tip Number 1
Network with professionals in the biotech and data science fields. Attend industry conferences, webinars, or local meetups in Cambridge to connect with potential colleagues and learn about the latest trends in drug discovery.
✨Tip Number 2
Showcase your technical skills by working on relevant projects or contributing to open-source initiatives. This will not only enhance your portfolio but also demonstrate your practical experience with tools like Python and R, which are crucial for this role.
✨Tip Number 3
Stay updated on the latest advancements in oncology and machine learning. Follow key publications and thought leaders in the field to ensure you can discuss current trends and innovations during interviews.
✨Tip Number 4
Prepare to discuss how you've collaborated with cross-functional teams in the past. Highlight specific examples where your data-driven insights influenced decision-making in drug development, as this is a key aspect of the role.
We think you need these skills to ace Data Scientist | Cambridge | Biotech (Drug Discovery)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in the biotech sector and drug discovery. Emphasise any projects or roles where you've applied machine learning or statistical techniques to biological datasets.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for cancer therapies and your understanding of the role. Mention specific experiences that align with the key responsibilities, such as collaborating with cross-functional teams or developing predictive models.
Highlight Technical Skills: Clearly list your proficiency in programming languages like Python and R, along with any relevant libraries you’ve used. Provide examples of how you've applied these skills in previous roles, especially in relation to multi-omics data analysis.
Showcase Communication Abilities: Since the role requires presenting findings to various stakeholders, include examples of how you've effectively communicated complex data insights in past positions. This could be through presentations, reports, or collaborative projects.
How to prepare for a job interview at SoCode
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in programming languages like Python and R, as well as your experience with data analysis libraries such as TensorFlow and scikit-learn. Be prepared to discuss specific projects where you've applied these skills, especially in the context of drug discovery or oncology.
✨Demonstrate Collaborative Experience
Since the role involves working with cross-functional teams, share examples of how you've successfully collaborated with biologists, chemists, or other scientists. Emphasise your ability to communicate complex data findings to both scientific and non-scientific audiences.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, particularly in relation to large-scale datasets and predictive modelling. Think of scenarios where you've tackled challenges in data analysis or model optimisation, and be ready to explain your thought process.
✨Stay Updated on Industry Trends
Show your passion for the field by discussing recent advancements in data science, machine learning, and computational biology. Being knowledgeable about current trends will demonstrate your commitment to innovation and continuous learning in the biotech sector.
