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- Tasks: Design and build AI solutions using Azure technologies while engaging directly with clients.
- Company: High-growth data consultancy known for rapid delivery and innovative solutions.
- Benefits: Competitive contract rates, hybrid work model, and opportunities for long-term incentives.
- Why this job: Shape client outcomes and work on cutting-edge Azure and AI projects.
- Qualifications: Strong experience in Data Science, Python, SQL, and Azure environments.
- Other info: Dynamic, low-bureaucracy environment with excellent career growth potential.
The predicted salary is between 60000 - 80000 £ per year.
Location: UK (client-facing, hybrid as required)
Type: Contract
Level: Senior / Consultant
Overview
We are working with a high-growth, Microsoft-aligned data consultancy delivering modern data platform and AI solutions across enterprise clients. Operating at the forefront of the Azure ecosystem (Fabric, Databricks, Synapse), the business is known for its rapid delivery model, providing tangible value to clients in weeks, not months, while embedding capability within client teams.
They are looking for a Data Scientist who can combine strong technical capability with a consulting mindset, working directly with stakeholders to shape, deliver, and scale data-driven solutions.
The Role
This is not a traditional back-office data science role. You will operate as a client-facing consultant, often working independently or in small teams, delivering high-impact solutions and guiding clients through their data and AI journey.
You will be expected to:
- Engage directly with business and technical stakeholders (including senior leadership)
- Translate ambiguous requirements into actionable data science solutions
- Rapidly prototype and deliver models that create measurable business value
- Iterate and scale solutions into production-ready systems
- Upskill and mentor client teams as part of delivery
Key Responsibilities
- Design and build machine learning / AI solutions using Azure-based technologies
- Work across the full lifecycle: problem definition, data exploration, model development, deployment and optimisation
- Deliver solutions in fast-paced, iterative environments (weeks rather than months)
- Communicate insights clearly to both technical and non-technical stakeholders
- Lead workshops, assessments, and client engagements
- Support the development of reusable frameworks and best practices
Key Skills & Experience
- Strong experience in Data Science / Machine Learning roles
- Hands-on expertise with: Python (Pandas, NumPy, Scikit-learn, etc.), SQL
- Experience working within Azure data environments, ideally: Azure Machine Learning, Databricks, Microsoft Fabric / Synapse
- Experience deploying models into production environments
- Strong understanding of: feature engineering, model evaluation, MLOps principles
- Consulting / Soft Skills (Critical)
- Proven ability to work directly with clients and stakeholders
- Strong communication and presentation skills
- Comfortable operating in ambiguous, fast-moving environments
- Ability to think on your feet and adapt in real time
- Experience leading or contributing to client-facing engagements
Desirable
- Experience in consultancy or client-facing roles
- Exposure to modern data platform architectures (lakehouse, medallion, etc.)
- Experience working with Fabric / Databricks at scale
- Knowledge of GenAI / LLM use cases
- Experience mentoring or leading junior team members
Why Join
- Work on cutting-edge Azure and AI projects
- Operate in a high-impact, low-bureaucracy environment
- Opportunity to take ownership and shape client outcomes
- Be part of a high-growth consultancy with a clear trajectory
- Opportunity for long-term incentives aligned to business growth
Data Scientist in Plymouth employer: Morgan McKinley
Contact Detail:
Morgan McKinley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Plymouth
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the data science game. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those using Azure technologies. This is your chance to demonstrate your hands-on expertise and problem-solving abilities to potential employers.
✨Tip Number 3
Prepare for interviews by practising common data science scenarios. Think about how you’d translate ambiguous requirements into actionable solutions. Being able to articulate your thought process will impress those client-facing stakeholders!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Data Scientist in Plymouth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Data Scientist role. Highlight your experience with Azure, Python, and any client-facing projects you've worked on. 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 the perfect fit for this consultancy role. Share specific examples of how you've delivered data-driven solutions and engaged with stakeholders in the past.
Showcase Your Technical Skills: Don’t just list your skills; demonstrate them! If you’ve built models or worked with Azure technologies, mention those projects. We love seeing real-world applications of your expertise, so make it count!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Morgan McKinley
✨Know Your Tech Inside Out
Make sure you’re well-versed in the key technologies mentioned in the job description, like Azure Machine Learning, Databricks, and Python libraries. Brush up on your knowledge of MLOps principles and be ready to discuss how you've applied these in real-world scenarios.
✨Prepare for Client Engagements
Since this role is client-facing, think about past experiences where you've interacted with stakeholders. Be prepared to share examples of how you translated complex data science concepts into actionable insights for non-technical audiences. This will show your consulting mindset.
✨Showcase Your Problem-Solving Skills
Expect to tackle some ambiguous scenarios during the interview. Practice articulating your thought process when defining problems and developing solutions. Highlight your ability to iterate quickly and deliver results in fast-paced environments.
✨Demonstrate Leadership and Mentorship
If you have experience mentoring or leading teams, make sure to highlight this. Discuss how you've upskilled others in data science practices and how you can bring that same energy to the consultancy. This will resonate well with their focus on embedding capability within client teams.