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- Tasks: Lead a team to innovate healthcare solutions using data science and machine learning.
- Company: Join a top-rated insurance company with a stellar reputation in the UK and beyond.
- Benefits: Enjoy a hybrid work model, excellent benefits, and a supportive working environment.
- Why this job: Shape the future of healthcare while mentoring junior talent in a dynamic team.
- Qualifications: Experience in leading data science projects, strong Python skills, and good communication abilities required.
- Other info: Must have a valid UK work permit; opportunity to make a real impact.
The predicted salary is between 43200 - 72000 £ per year.
Lead Data Scientist – Bristol THIS IS A HYBRID ROLE, YOU MUST BE ABLE TO COMMUTE TO BRISTOL EXCELLENT BENEFITS PACKAGE AND WORKING ENVIRONMENT The Company: The company is a leader in its field and is an Insurance business with an excellent reputation both in the UK and abroad. The Role: Lead Data Scientist To lead the 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 a dynamic and forward-thinking team, to shape the future of healthcare. What you’ll be doing: Lead a 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, preprocessing, 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 optimise business operations. Mentor and coach junior data scientists, fostering a culture of continuous learning, innovation, and excellence in data science practices. Ideally you will have: 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. This is an excellent opportunity to join a dynamic business and make a difference. Please contact me for more info. YOU MUST HAVE A VALID WORK PERMIT TO WORK IN THE UK #J-18808-Ljbffr
Lead Data Scientist - Bristol employer: Dietz & Lynch Capital
Contact Detail:
Dietz & Lynch Capital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - Bristol
✨Tip Number 1
Familiarise yourself with the latest trends in healthcare data science. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Network with professionals in the insurance and healthcare sectors. Attend relevant meetups or webinars to connect with potential colleagues and learn more about the challenges they face, which can help you tailor your approach.
✨Tip Number 3
Prepare to showcase your leadership skills. Think of specific examples where you've successfully led a team or project, especially in data science, as this role requires mentoring junior scientists and driving innovation.
✨Tip Number 4
Brush up on your communication skills. Be ready to explain complex data science concepts in simple terms, as you'll need to convey insights to non-technical stakeholders effectively.
We think you need these skills to ace Lead Data Scientist - Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in leading teams and developing AI projects. Emphasise your skills in Python and data science packages like Scikit-learn and TensorFlow.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about the healthcare industry and how your background aligns with the company's goals. Mention specific examples of your leadership experience and successful projects.
Showcase Your Technical Skills: Include a section in your application that details your technical skills, especially those related to machine learning and data analytics. Highlight any experience with MLOps and working in mixed technical teams.
Prepare for Interviews: Be ready to discuss your previous projects in detail, particularly how you have mentored junior data scientists and communicated complex findings to non-technical stakeholders. Practice articulating your thought process and problem-solving approach.
How to prepare for a job interview at Dietz & Lynch Capital
✨Showcase Your Leadership Skills
As a Lead Data Scientist, you'll be expected to lead a team. Be prepared to discuss your previous experiences in mentoring and coaching junior data scientists. Highlight specific examples where you successfully guided a team through complex projects.
✨Demonstrate Technical Proficiency
Make sure to brush up on your knowledge of Python and relevant data science packages like Scikit-learn, Keras, and TensorFlow. Be ready to discuss how you've applied these tools in past projects, especially in developing machine learning models.
✨Understand the Business Context
Since the role is within the insurance sector, it’s crucial to understand how data science can drive business value in this industry. Prepare to discuss how your work can impact decision-making and improve healthcare services, using both quantitative and qualitative metrics.
✨Communicate Complex Ideas Simply
You’ll need to explain complex scientific findings to non-technical stakeholders. Practice articulating your past projects in a way that is accessible to those without a technical background, focusing on the implications and benefits of your work.
