At a Glance
- Tasks: Scale advanced genomics analytics for drug discovery and disease understanding.
- Company: Join a pioneering team at the forefront of genomic research.
- Benefits: Competitive salary, clear career path, private health insurance, and hybrid working.
- Other info: Collaborative environment with continuous learning and growth opportunities.
- Why this job: Make a real impact in healthcare by translating genomic insights into effective solutions.
- Qualifications: Strong knowledge of genetics, experience with large datasets, and coding skills in Python or R.
The predicted salary is between 51750 - 63250 £ per year.
Overview
In this role you help scale and apply advanced genomics analytics to drug discovery and disease understanding.
You will work within a cross-disciplinary team of genetics, data science, and software engineering to process, QC, and analyze diverse genomic data types.
You’ll develop robust statistical and machine learning methods and contribute to production-ready software tools.
The role supports cutting-edge research that translates genomic insights into safer, more effective targets and preventive health insights.
- Pay / Benefits
- Competitive salary
- Clear career path
- Continuous learning
- Private health insurance
- Pension scheme
- Hybrid working
Responsibilities
- Identify and integrate new data types into the analytics platform for disease mechanism insights
- Develop production-quality code for data processing, transformation and quality control
- Apply and validate statistical and machine learning methods with a focus on robustness and reproducibility
- Collaborate with cross-disciplinary teams to interpret genomic data and drive drug target discovery
- Contribute to internal and external publications and presentations
- Keep up-to-date with innovations in genomics, functional genomics, and statistical genetics
- Lead data integration initiatives and, for IC3 level, coordinate multi-source functional genomics projects
- Key requirements
- Strong knowledge of human genetics and functional or clinical genomics
- Experience analyzing large-scale biological datasets using statistical and ML methods
- Proficient coding in Python and/or R with good software development practices
- Experience processing data from functional genomics, molecular and expression atlases, genomic annotations, and curated resources
- Experience running tools/workflows in scalable systems (Linux HPC or cloud)
- Experience with version control and CI/CD
- Experience working in remote/cloud environments (e. g., AWS)
- Ph D or postgraduate degree in relevant field
- Collaborative and cross-disciplinary teamwork
- Strong communication and presentation abilities
- Proactive problem solving and attention to reproducibility
- Python
- R
- machine learning
Data Scientist employer: Genomics
At Genomics, we pride ourselves on being an exceptional employer, offering a dynamic and inclusive work culture that fosters innovation and collaboration. With competitive salaries, clear career progression paths, and a commitment to continuous learning, our employees thrive in a supportive environment that prioritises their wellbeing. Located in vibrant cities like Oxford and London, we provide flexible working options and unique benefits such as enhanced family leave and a 'Bank Your Bank Holiday' programme, ensuring that our team members can balance their professional and personal lives effectively.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist at Genomics.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Genomics.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist at Genomics, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Genomics, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Genomics. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Genomics
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Genomics!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
