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For Companies At a Glance
- Tasks: Transform complex data into impactful AI solutions and collaborate with cross-functional teams.
- Company: Fast-growing tech-driven organisation focused on AI-enabled solutions.
- Benefits: Competitive salary, health benefits, life assurance, and pension.
- Why this job: Make a real-world impact with your Data Science skills in a dynamic environment.
- Qualifications: Strong Python and SQL skills, experience with data pipelines and cloud environments.
- Other info: Hybrid role with excellent career growth opportunities and a supportive team culture.
The predicted salary is between 75000 - 92000 £ per year.
Location: London (Hybrid – 3 days onsite)
Salary - £75,000 to £92,000+
Health, Life Assurance, Pension
Are you a Data Science professional who loves solving real operational challenges, not just experimenting in notebooks? Do you enjoy working with production‑grade data pipelines, cross‑functional product teams, and high‑impact AI initiatives? I am looking for a Data Scientist to help shape advanced analytics and AI capabilities for large‑scale operational environments. You’ll be joining a fast‑growing tech‑driven organisation delivering AI‑enabled solutions that must run reliably across multiple operating companies — no proofs of concept, no throwaway prototypes. If you're excited by building intelligent systems that get deployed for real, this role could be exactly what you’re looking for.
What You’ll Be Doing
- Develop advanced models and analytical approaches that transform complex operational data into real‑world impact.
- Work closely with Data Engineers who build enterprise‑grade ETL/ELT pipelines, ensuring your Data Science outputs are scalable and production-ready from day one.
- Collaborate tightly with Product, Engineering, Analysts, and stakeholders to integrate AI solutions directly into operational workflows, not just analytical environments.
- Shape data architectures that support multi‑OpCo, multi‑tenant deployments at scale.
- Influence technical direction and embed rapidly into new teams to deliver high‑impact outcomes under real deadlines and ambiguity.
This is Data Science with true end‑to‑end ownership from modelling to deployment.
What You Bring
- Strong Python and SQL experience, including performance tuning in production environments.
- A solid grounding in Data Science techniques: statistical modelling, machine learning, optimisation, or operational analytics.
- Experience working alongside Data Engineers using tools like Airflow, dbt, Glue or similar orchestration technologies.
- Deep familiarity with cloud environments (AWS strongly preferred), including data, security, and infrastructure components.
Is This You? Ask Yourself…
- Do you want to practice Data Science where your work actually reaches production — quickly and reliably?
- Do you enjoy working in fast‑moving, cross‑functional product squads?
- Do you love the challenge of taking messy, complex data and turning it into robust, scalable AI solutions?
- Are you excited by environments where you influence architecture, strategy, and hands‑on delivery?
- Do you want your Data Science work to directly impact real‑world operational decisions — not sit in a slide deck?
Working Model
Hybrid role 3 days onsite in London collaborating directly with customer teams. Fast‑growth, supportive environment with strong engineering, AI, and product maturity.
Why This Role Stands Out
- You get to build Data Science solutions that genuinely reach production.
- You’ll join a team where technical excellence, rapid delivery, and impact are core values.
- You’ll work across multiple operating companies, solving high‑value problems with enterprise visibility.
- You’ll help shape the future of AI‑driven operational intelligence.
If this sounds like a role you would be interested in please get in touch with me, kumbirai.mafini@opus.com
Data Scientist | £92,000 | London | Hybrid employer: Opus Recruitment Solutions
Contact Detail:
Opus Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist | £92,000 | London | Hybrid
✨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those that demonstrate your ability to solve real-world problems with data. This will make you stand out when you apply.
✨Tip Number 3
Prepare for interviews by practising common data science scenarios and case studies. We recommend simulating the interview environment with friends or mentors to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Data Scientist | £92,000 | London | Hybrid
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience with Python, SQL, and any relevant data science techniques. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data science and how you’ve tackled real-world challenges. Let us know why you’re excited about building AI solutions that make an impact.
Showcase Your Projects: If you've worked on projects that involved production-grade data pipelines or AI initiatives, don’t hold back! Include links or descriptions of your work to demonstrate your hands-on experience and problem-solving skills.
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 the best chance to showcase your talents to our team!
How to prepare for a job interview at Opus Recruitment Solutions
✨Know Your Data Science Stuff
Make sure you brush up on your Python and SQL skills, especially performance tuning in production environments. Be ready to discuss specific projects where you've transformed complex data into actionable insights, as this will show your practical experience.
✨Understand the Company’s Needs
Research the company’s AI initiatives and operational challenges they face. Tailor your answers to demonstrate how your skills can directly address these issues, especially in terms of building scalable solutions that integrate seamlessly into their workflows.
✨Showcase Collaboration Skills
Since this role involves working closely with Data Engineers and cross-functional teams, prepare examples of how you've successfully collaborated in the past. Highlight any experience with tools like Airflow or dbt, as well as your ability to influence technical direction.
✨Be Ready for Real-World Scenarios
Expect questions that assess your problem-solving abilities in real-world situations. Think about how you've tackled messy data and turned it into robust AI solutions, and be prepared to discuss your thought process and the impact of your work.