At a Glance
- Tasks: Join a team of scientists tackling genetic data for better health outcomes.
- Company: A pioneering health tech company revolutionising personalised medicine through genomics.
- Benefits: Enjoy hybrid working, 25 days holiday, and comprehensive health insurance.
- Other info: Participate in charity giving and enjoy various company socials throughout the year.
- Why this job: Make a real impact on healthcare while collaborating with leading scientists in an inclusive environment.
- Qualifications: Experience in genetic analyses and statistical programming is essential.
The predicted salary is between 36000 - 60000 £ per year.
Location: Oxford or London (Hybrid)
The Mission: Why We Exist
Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare. We are united by a single vision to help people live longer healthier lives, using the power of genomics. Genomics aims to help people live longer, healthier lives in two ways: super-charging drug discovery and development for novel treatments with our AI-enabled advanced genetic analytics platform, and by helping people understand their personal risk of common chronic diseases through polygenic risk scores - giving doctors and health systems the chance to get the right people into the right prevention, screening and treatment programmes at the right time.
A Day in the Life
As a Scientist, you'll drive innovation and collaboration, devising groundbreaking scientific approaches that help to shape team direction. You'll communicate your discoveries effectively, and be a spearhead in leading transformative projects across the team. You'll forge cutting-edge methods to craft Polygenic Risk Scores by harnessing genomic, real-world and clinical data. Using a strategic approach, you will utilise advanced statistical techniques to prioritise therapeutics targets to unveil new treatment possibilities. Success here demands a robust grasp of statistical human genetics applied inventively. You'll excel in unraveling complex genomic data and possess a knack for uncovering key insights, whilst working collectively with your highly skilled team.
Who You Are
- Experience in performing foundational genetic association analyses (e.g., GWAS; PRS)
- Strong competency in statistical programming (e.g., R, Python) sufficient to enable large-scale genomic data analysis
- Experience in data mining and/or management of large datasets.
- Confident in engaging with a variety of stakeholders, contributing and supporting in the delivery of presentations to customers.
Your Package
We are committed to providing a transparent, supportive, and rewarding work environment.
COMPENSATION & GROWTH
- Competitive Salary: Salaries are externally benchmarked annually to ensure top-of-market compensation.
- Clear Career Path: A straightforward, open progression framework means you'll always know the path to promotion and how to achieve your next career goal.
- Continuous Learning: Including external courses and a wide library of L&D materials, because your growth is our success.
WELLBEING & TIME OFF
- Holiday: 25 days annual leave, plus bank holidays, plus an extra 3-day company-wide shutdown at year-end.
- Financial & Health Security: Robust benefits including a market-leading pension scheme, comprehensive private health insurance for you and your family with NO excess, critical illness, and life assurance.
- Enhanced Leave: Enhanced paid family leave to support all new parents.
WORK ENVIRONMENT & CULTURE
- Flexible Working: Hybrid Working (e.g., From our London, Oxford Office)
- Truly Inclusive Time Off: Our 'Bank Your Bank Holiday' program allows you to exchange public holidays for dates that hold personal or cultural significance to you.
- Vibrant Social Culture: From regular Town Halls and team picnics to organised sports events, our social committee ensures frequent opportunities to connect and celebrate.
- Green Commute: Cycle-to-Work scheme and convenient office locations near major transport hubs.
We are dedicated to creating a diverse environment and are proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
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Scientist in Oxford employer: Genomics
At Genomics, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our hybrid work environment allows for flexibility while providing ample opportunities for professional growth and development, particularly in cutting-edge fields like AI and data science. Join us to be part of a mission-driven team that values your contributions and supports your career aspirations in a dynamic and impactful setting.
StudySmarter Expert Advice🤫
We think this is how you could land Scientist in Oxford
✨Tip Number 1
Familiarise yourself with the latest advancements in statistical genetics and genomics. Being well-versed in current research and methodologies will not only boost your confidence but also demonstrate your passion for the field during discussions.
✨Tip Number 2
Network with professionals in the health tech and genomics sectors. Attend relevant conferences, webinars, or local meetups to connect with potential colleagues and learn about the latest trends, which can give you an edge in interviews.
✨Tip Number 3
Prepare to discuss your experience with specific statistical programming languages like R and Python. Be ready to share examples of how you've used these tools in past projects, as practical knowledge is highly valued in this role.
✨Tip Number 4
Practice your communication skills, especially in explaining complex genetic concepts to non-experts. This will be crucial when sharing insights with stakeholders, so consider role-playing scenarios to enhance your clarity and effectiveness.
We think you need these skills to ace Scientist in Oxford
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in statistical human genetics and any relevant projects you've worked on, such as genetic association analyses or statistical programming. Use keywords from the job description to align your skills with what the company is looking for.
Craft a Compelling Cover Letter:In your cover letter, express your passion for genomics and personalised medicine. Discuss how your background in statistical genetics can contribute to the company's mission of improving healthcare. Be specific about your achievements and how they relate to the role.
Showcase Communication Skills:Since effective communication is key for this role, include examples of how you've successfully shared complex findings with stakeholders in the past. This could be through presentations, reports, or collaborative projects.
Highlight Flexibility and Teamwork:Mention your ability to work both in-office and remotely, as well as your experience collaborating with teams. Emphasise your adaptability and willingness to engage with colleagues to solve scientific challenges.
How to prepare for a job interview at Genomics
✨Showcase Your Statistical Skills
Make sure to highlight your experience with statistical genetics, especially in performing foundational genetic association analyses like GWAS. Be prepared to discuss specific projects where you applied these skills and the impact they had.
✨Demonstrate Effective Communication
As an effective communicator, you should be ready to explain complex genomic concepts in simple terms. Practice summarising your findings and how they can benefit stakeholders, as this will be crucial in your role.
✨Familiarise Yourself with Their Mission
Understand the company's mission to revolutionise healthcare through genomics. Be prepared to discuss how your background and interests align with their goals, and how you can contribute to their vision of personalised medicine.
✨Prepare for Technical Questions
Expect technical questions related to statistical programming languages like R and Python. Brush up on your coding skills and be ready to solve problems or analyse data during the interview to demonstrate your proficiency.
