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- Tasks: Lead a team of data scientists to innovate healthcare solutions using AI and machine learning.
- Company: Join a dynamic team focused on transforming the healthcare industry through data science.
- Benefits: Enjoy hybrid working options and a competitive salary of £90,000.
- Why this job: Make a real impact in healthcare while mentoring junior talent in a forward-thinking environment.
- Qualifications: Proven experience in leading data science projects and strong skills in Python and AI frameworks.
- Other info: Full UK working rights required; no sponsorship available.
The predicted salary is between 54000 - 126000 £ per year.
- Job Title: Lead Data Scientist – ML & AI projects
- Salary: £90,000
- Location: Bristol (hybrod working)
Unfortunately, no sponsorship available with this client so full UK working rights required
Our client is seeking to recruit a new Lead Data Scientist to lead data science initiatives and drive innovation in the healthcare industry. You'll have the opportunity to leverage your expertise in data analysis and machine learning within our dynamic and forward-thinking team, to shape the future of healthcare. If you're passionate about making a real impact and are ready to lead a team of talented data scientists, we want to hear from you.
What you'll be doing:
- Lead a relatively small team of data scientists in developing and implementing advanced data analytics, machine learning and traditional and generative AI solutions, to address complex challenges in healthcare.
- Collaborate with cross-functional teams to identify business opportunities, define data science strategies, and drive the development of innovative products and services.
- Oversee the end-to-end process of data collection, pre-processing, analysis, and model development to derive actionable insights and improve decision-making.
- Drive the development and deployment of scalable and efficient machine learning models and algorithms to enhance healthcare services and optimize business operations.
- Mentor and coach junior data scientists, fostering a culture of continuous learning, innovation, and excellence in data science practices.
What you'll bring:
- In depth experience coaching and leading junior data scientists within a senior data science role.
- Demonstrable experience of developing complex AI projects with minimal supervision, working in line with best practices.
- Working knowledge of extracting business value from data science methods using both quantitative and qualitative metrics.
- Strong mathematical and statistical background.
- Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark.
- Experience and understanding of mixed technical teams such as engineering, architects, business analysts.
- Familiar with MLOps industry best practices.
- Good stakeholder communication skills with proven ability to translate complex scientific findings to non-technical stakeholders.
- Understanding of the financial industry, in particular insurance, would be advantageous.
If this sounds like you, please make an application and we'll be in touch.
Data Scientist employer: GradBay
Contact Detail:
GradBay Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Make sure to showcase your leadership experience in data science. Highlight any previous roles where you mentored junior data scientists or led a team, as this is crucial for the Lead Data Scientist position.
✨Tip Number 2
Familiarize yourself with the latest trends in machine learning and AI, especially in the healthcare sector. Being able to discuss recent advancements or case studies during your interview can set you apart from other candidates.
✨Tip Number 3
Prepare to demonstrate your technical skills in Python and relevant data science packages. You might be asked to solve a problem or explain your approach to developing machine learning models, so practice articulating your thought process.
✨Tip Number 4
Since stakeholder communication is key, think of examples where you've successfully translated complex data findings to non-technical audiences. This will show your ability to bridge the gap between technical and business teams.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in leading data science teams and your expertise in machine learning and AI projects. Use specific examples that demonstrate your ability to drive innovation in the healthcare industry.
Craft a Compelling Cover Letter: In your cover letter, express your passion for making an impact in healthcare through data science. Mention your leadership experience and how you can mentor junior data scientists, as well as your familiarity with MLOps best practices.
Showcase Relevant Projects: Include details of complex AI projects you've developed, emphasizing your role and the outcomes achieved. Highlight your proficiency in Python and relevant data science packages like Scikit-learn and TensorFlow.
Prepare for Interviews: Be ready to discuss your approach to leading data science initiatives and how you translate complex findings to non-technical stakeholders. Prepare examples of how you've collaborated with cross-functional teams to identify business opportunities.
How to prepare for a job interview at GradBay
✨Showcase Your Leadership Skills
As a Lead Data Scientist, you'll be expected to mentor and guide junior team members. Be prepared to discuss your previous experiences in leading teams, coaching others, and fostering a culture of innovation. Highlight specific examples where your leadership made a difference.
✨Demonstrate Technical Expertise
Make sure to brush up on your knowledge of Python and relevant data science packages like Scikit-learn, Keras, TensorFlow, and PySpark. Be ready to discuss your experience with machine learning models and how you've applied them in real-world scenarios, especially in healthcare.
✨Communicate Complex Ideas Simply
You will need to translate complex scientific findings to non-technical stakeholders. Practice explaining your past projects in simple terms, focusing on the business value and impact rather than just the technical details. This will showcase your stakeholder communication skills.
✨Understand the Healthcare Context
Since this role is focused on the healthcare industry, familiarize yourself with current challenges and innovations in this field. Be prepared to discuss how your data science expertise can address these challenges and improve healthcare services.
