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- Tasks: Design and implement machine learning models and MLOps frameworks for impactful data solutions.
- Company: Join Acuity Analytics, a global leader in digital transformation and data insights.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Work in a dynamic team with a focus on personal and professional development.
- Why this job: Make a real impact by solving complex data challenges in a collaborative environment.
- Qualifications: Strong Python skills, experience with ML models, and excellent communication abilities.
The predicted salary is between 50000 - 70000 £ per year.
Please note that for this role, you must be based in the UK, Malta, Bulgaria, or Portugal.
About us
Ascent has recently been acquired by Acuity Analytics. This is both a significant milestone for us and a tremendous opportunity for you. Acuity Analytics is a business with a strong global reputation, an impressive client base and ambitious growth plans. We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organisations. To our customers, we bring a partnership that provides the talent, technology and capability to enhance performance and operational efficiency.
About the role
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 required
- Thorough knowledge of the Python language
- Experience in training, tuning and refining ML models in Python (mainly scikit learn and tree based models) (Core ML)
- Working understanding of end to end machine learning pipelines
- 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 (Fabric / Azure nice to have)
- Nice to have: Financial / Investment understanding, experience with cashflow & pricing models
What you will do
- Collaborate closely with key stakeholders and a team of data scientists
- Design and implement new project code and MLOps frameworks for the deployment of models in production
- Build machine learning models for financial / investment company
- 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 productionised pipelines, addressing any issues in a timely manner to ensure smooth and continuous operation
Why join us
People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive.
Data Scientist (Python+MLOps) employer: Acuity Analytics
Contact Detail:
Acuity Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Python+MLOps)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. Building relationships can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and MLOps. This gives you a chance to demonstrate your expertise and makes you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data science questions and scenarios. Think about how you can explain complex concepts in simple terms, as you'll need to communicate effectively with non-specialists.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Data Scientist (Python+MLOps)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your Python skills, MLOps experience, and any relevant projects you've worked on. We want to see how your background aligns 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. Be sure to mention specific experiences that relate to the job description.
Showcase Your Communication Skills: Since you'll be translating complex data problems into practical solutions, it's crucial to demonstrate your communication skills in your application. Use clear and concise language to convey your ideas and experiences.
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 our team!
How to prepare for a job interview at Acuity Analytics
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially around libraries like scikit-learn and tree-based models. Be ready to discuss your experience with training and tuning ML models, as this will likely come up during the interview.
✨Understand MLOps and DevOps Frameworks
Familiarise yourself with end-to-end machine learning pipelines and MLOps practices. Be prepared to share examples of how you've implemented these frameworks in past projects, as this will demonstrate your hands-on experience and operational excellence.
✨Communicate Like a Pro
Since you'll be working closely with stakeholders, practice explaining complex technical concepts in simple terms. Think of examples where you've successfully communicated data science ideas to non-specialists, as this will showcase your consultative mindset.
✨Show Your Collaborative Spirit
Highlight your experience in collaborating with teams and clients. Prepare to discuss how you've built strong relationships in previous roles and how you've identified opportunities for data science to add value, as this aligns perfectly with what they're looking for.