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- Tasks: Analyse data, develop predictive models, and communicate insights to drive business decisions.
- Company: Join a dynamic employer focused on innovative ML & AI solutions for health and well-being.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact using data to improve lives while working in a collaborative environment.
- Qualifications: Experience in data science, strong Python skills, and a solid understanding of statistical methods required.
- Other info: No visa sponsorship available; applicants must have the right to work in the UK.
The predicted salary is between 50000 - 65000 £ per year.
Competitive annual salary of between £50,000 and £65,000 dependent on experience.
Hybrid working - Bristol office base (2 days a week currently, expected to increase to 3 days).
No Visa Sponsorship Available - All applicants must have full and indefinite right to work in the UK.
Working with an exceptional employer, looking to recruit a highly skilled individual to join their dynamic and innovative Data Science team. This role will give you the opportunity to leverage your expertise in data analysis and machine learning to drive actionable insights and contribute to the development of cutting-edge solutions that improve the health and well-being of their customers.
What you'll be doing:
- Gather and clean large volumes of structured and unstructured data from various sources.
- Apply statistical, machine learning and traditional and generative AI techniques to analyse data, identify patterns, and develop predictive models.
- Create visual representations of data to communicate insights and findings to non-technical stakeholders.
- Interpret data analysis results to provide actionable insights and recommendations for business decisions.
- Work closely with cross-functional teams to understand business needs, develop solutions, and implement data-driven strategies.
- Stay updated with the latest trends and advancements in data science, machine learning, and related technologies to improve methodologies and processes.
- Ensure compliance with data privacy regulations and ethical standards in handling sensitive information.
What you'll bring:
- Previous applied experience within a data science role.
- Demonstrable knowledge of extracting business value from data science using both quantitative and qualitative metrics.
- Strong mathematical and statistical background.
- An ability to understand and translate data into actionable insights for the business.
- Strong working knowledge of Python and data science packages such as Scikit-learn, Keras, TensorFlow, and PySpark.
- Good understanding of industry standard MLOps capabilities.
- Understanding of the financial industry, in particular insurance, would be advantageous.
If you're excited about the prospect of using data to make a meaningful difference in people's lives, we want to hear from you!
Data Scientist – Bristol employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist – Bristol
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and AI, especially those relevant to the health and well-being sectors. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Network with professionals in the data science field, particularly those who work in the financial industry or have experience with insurance. Engaging in conversations can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss specific projects where you've applied statistical and machine learning techniques. Be ready to explain your thought process, the challenges you faced, and how your contributions led to actionable insights.
✨Tip Number 4
Showcase your proficiency in Python and relevant data science packages by discussing any personal projects or contributions to open-source initiatives. This practical experience can set you apart from other candidates.
We think you need these skills to ace Data Scientist – Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with machine learning and AI projects. Use specific examples that demonstrate your ability to extract business value from data.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your skills align with their needs, especially your experience with Python and data science packages like Scikit-learn and TensorFlow.
Showcase Your Projects: If you have worked on any relevant projects, include them in your application. Describe the challenges you faced, the techniques you used, and the outcomes achieved, particularly in relation to health and well-being.
Highlight Continuous Learning: Mention any recent courses or certifications related to data science, machine learning, or MLOps. This shows your commitment to staying updated with industry trends and advancements.
How to prepare for a job interview at Datatech Analytics
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and data science packages like Scikit-learn, Keras, TensorFlow, and PySpark. Bring examples of projects where you've applied these tools, as practical demonstrations can impress the interviewers.
✨Understand the Business Context
Familiarise yourself with the financial industry, particularly insurance, as this knowledge could set you apart. Be ready to explain how your data insights can drive business decisions and improve customer outcomes.
✨Communicate Clearly
Since you'll need to present complex data findings to non-technical stakeholders, practice explaining your analysis in simple terms. Use visual aids if possible, as they can help convey your insights more effectively.
✨Stay Updated on Trends
Demonstrate your commitment to continuous learning by discussing recent advancements in data science and machine learning. Mention any relevant courses or certifications you've completed to show you're proactive about your professional development.
