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- Tasks: Lead a dynamic data science team to transform complex data into actionable insights.
- Company: Join Portal Biotech, a leader in innovative biomedical technology.
- Benefits: Competitive salary, career growth, and opportunities for innovation.
- Why this job: Make a real impact in the biotech field with cutting-edge machine learning techniques.
- Qualifications: Proven leadership in data science and extensive programming experience required.
- Other info: Collaborative environment with opportunities to represent the company at industry events.
The predicted salary is between 72000 - 108000 ÂŁ per year.
We are looking for an exceptional individual to lead our data science group: to provide strategic and technical leadership in delivering our analysis infrastructure and developing the tools and algorithms that transform complex, noisy timeâseries data into actionable insights. You will set the vision for data science across the organisation, ensuring the effective integration of advanced machine learning techniques into our core nanopore technologies. Working with senior leadership, you'll align data science priorities with company goals, manage a highâperforming team, and cultivate an environment that drives innovation in biomedical discovery.
Tasks And Responsibilities
- Define and execute the organisation's data science strategy in line with scientific and commercial objectives.
- Lead and grow a multidisciplinary data science team, fostering technical excellence and career development.
- Oversee the design, implementation, and integration of scalable analytical models into production pipelines.
- Champion best practices in reproducibility, validation, and scientific rigour.
- Collaborate with internal and external stakeholders to identify opportunities for dataâdriven innovation.
- Represent the company at conferences, workshops, and strategic partnerships.
Qualifications
- Demonstrated leadership in managing data science teams and delivering complex projects.
- Extensive programming and modelling experience in Python (NumPy, PyTorch/TensorFlow, SciPy, pandas).
- Deep expertise in machine learning for timeâseries and probabilistic modelling.
- Strong record of translating cuttingâedge research into production systems.
- Advanced degree (PhD preferred) in a quantitative discipline.
- 10+ years relevant experience, preferably in an industry environment.
- Excellent communication skills with the ability to influence at all organisational levels.
Desirable
- Proven experience in biological/biomedical data domains.
- Established network in the computational biology/ML research community.
- Contributions to highâimpact publications, patent applications or openâsource projects.
- Experience navigating regulatory frameworks in biotech/healthcare.
Team Lead, Data science in London employer: Portal Biotech
Contact Detail:
Portal Biotech Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Team Lead, Data science in London
â¨Tip Number 1
Network like a pro! Get out there and connect with folks in the data science and biotech communities. Attend conferences, workshops, and meetups to make those valuable connections that could lead to your next big opportunity.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and time-series data. This will give potential employers a taste of what you can bring to the table.
â¨Tip Number 3
Donât just apply â engage! When you find a role that excites you, reach out to current employees on LinkedIn. Ask them about their experiences and get insider tips on the company culture and expectations.
â¨Tip Number 4
Keep it real during interviews! Be prepared to discuss your leadership style and how youâve driven innovation in past roles. Show them youâre not just a tech whiz but also a great team player who can inspire others.
We think you need these skills to ace Team Lead, Data science in London
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Team Lead, Data Science role. Highlight your leadership experience and technical expertise in Python and machine learning, as these are key for us.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for our data science team. Share specific examples of how you've led teams and delivered complex projects, and donât forget to mention your passion for biomedical innovation!
Showcase Your Achievements: When detailing your past roles, focus on quantifiable achievements. Did you improve a process or lead a successful project? We want to see how youâve made an impact in your previous positions.
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way for us to receive your application and ensures youâre considered for this exciting opportunity to lead our data science group!
How to prepare for a job interview at Portal Biotech
â¨Know Your Data Science Strategy
Before the interview, make sure you understand the company's data science strategy and how it aligns with their scientific and commercial objectives. Be ready to discuss how your vision can enhance their existing framework and drive innovation.
â¨Showcase Your Leadership Skills
Prepare examples of how you've successfully led data science teams in the past. Highlight specific projects where you fostered technical excellence and career development, as this will demonstrate your capability to manage and grow a high-performing team.
â¨Demonstrate Technical Expertise
Brush up on your programming skills, especially in Python and relevant libraries like NumPy and TensorFlow. Be prepared to discuss your experience with machine learning techniques, particularly in time-series and probabilistic modelling, as this is crucial for the role.
â¨Communicate Effectively
Practice articulating complex ideas clearly and concisely. Since excellent communication skills are essential for influencing at all organisational levels, think about how you can convey your thoughts on data-driven innovation and collaboration with stakeholders.
