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- Tasks: Design and implement robust ML pipelines, collaborating with stakeholders to solve data challenges.
- Company: Forward-thinking tech company focused on data-driven solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Make a real impact by leveraging data science to drive business success.
- Qualifications: Expertise in Python, MLOps, and strong communication skills.
- Other info: Dynamic team environment with excellent career advancement potential.
The predicted salary is between 43200 - 72000 £ per year.
In this role you’ll work on the design and implementation of deploying models into production, ensuring robust and maintainable pipelines. You’ll collaborate closely with stakeholders, building strong relationships to understand their challenges and translate complex data problems into practical, impactful solutions.
We’re looking for someone with strong expertise in Python, machine learning and MLOps, who can combine technical rigor with a consultative mindset. You’ll act as a trusted advisor, identifying opportunities where data science can add value, shaping roadmaps and raising the profile of Data Science in the wider business. This role blends hands-on implementation, operational excellence and strategic collaboration to deliver measurable business outcomes.
Skills And Experience- Thorough knowledge of the Python language
- Working understanding of MLOps and DevOps frameworks
- Daily use of GitHub, including version control, collaboration, testing and CI/CD
- Superb written and verbal communication skills and demonstrated ability to communicate complex technical and statistical ideas to non-specialists effectively
- Experience in cloud platforms such as Azure, AWS, and Databricks
- Collaborate closely with key stakeholders
- Refactor and optimise existing Python code to improve performance, readability, and maintainability
- Design and implement new project code and MLOps frameworks for the deployment of models in production
- Educate wider business on what Data Science is and increase Data Science team visibility
- Partner with client teams to identify opportunities where data science could add value, helping generate demand and shape a roadmap for future work
- Monitor existing production pipelines, addressing any issues in a timely manner to ensure smooth and continuous operation
Senior Data Scientist (ML Ops) in Bristol employer: Acuity Analytics
Contact Detail:
Acuity Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (ML Ops) in Bristol
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field and let them know you're on the lookout for opportunities. Attend meetups or webinars related to MLOps and Python to meet potential employers and learn about job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving MLOps and Python. Share it on platforms like GitHub and make sure to highlight any collaborative work that demonstrates your ability to communicate complex ideas effectively.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining your past projects and how you've solved real-world problems using data science. Remember, it's all about showing how you can add value to the team!
✨Tip Number 4
Don't forget to apply through our website! We have loads of exciting opportunities waiting for talented individuals like you. Tailor your application to highlight your experience with MLOps and your consultative mindset to stand out from the crowd.
We think you need these skills to ace Senior Data Scientist (ML Ops) in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Senior Data Scientist (ML Ops). Highlight your experience with Python, MLOps, and any cloud platforms you've worked with. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can add value to our team. Don’t forget to mention your consultative mindset and how you’ve successfully collaborated with stakeholders in the past.
Showcase Your Communication Skills: Since you'll be translating complex ideas for non-specialists, it's crucial to demonstrate your superb written communication skills. Use clear, concise language in your application to show us you can make complex topics accessible.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you're keen on joining the StudySmarter family!
How to prepare for a job interview at Acuity Analytics
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss specific projects where you've used Python, especially in relation to MLOps. They’ll likely want to hear about how you’ve optimised code for performance and maintainability.
✨Showcase Your MLOps Knowledge
Familiarise yourself with MLOps and DevOps frameworks. Be prepared to explain how you’ve implemented these in past roles. Think of examples where you’ve designed and deployed models into production, as this will demonstrate your hands-on experience.
✨Communicate Like a Pro
Since you'll be working closely with stakeholders, practice explaining complex data concepts in simple terms. Prepare to share examples of how you've successfully communicated technical ideas to non-specialists, as this is crucial for building strong relationships.
✨Be Ready to Collaborate
Think about times when you’ve partnered with client teams to identify opportunities for data science. Have a few examples ready that highlight your consultative mindset and how you’ve shaped roadmaps based on stakeholder needs. This will show you can add real value to their business.
