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- Tasks: Design and implement data workflows, build models, and extract insights from complex datasets.
- Company: Join a respected consultancy delivering impactful intelligence and data-led services.
- Benefits: Enjoy a supportive team environment with opportunities for growth and meaningful projects.
- Why this job: Work on real-world challenges in a high-trust setting while developing your skills.
- Qualifications: 6+ years in data science, strong Python skills, and experience with large datasets required.
- Other info: This is a full-time role with a focus on collaboration and innovation.
The predicted salary is between 43200 - 72000 ÂŁ per year.
This range is provided by developrec. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Direct message the job poster from developrec
Head of Data, UK | Geospatial/GIS | Tech She Can | Learning Python
My client is a respected consultancy delivering high-impact intelligence, research, and data-led services to both public and private sector organisations. As demand for their expertise grows, they are expanding their data science capability and looking for a capable Data Scientist to join the team.
This is an excellent opportunity for someone with hands-on experience in data science who is ready to apply their skills to meaningful, real-world challenges. You will be working on complex, sensitive projects within a high-trust environment, with the opportunity to grow alongside an experienced and supportive team.
Key Responsibilities:
- Design and implement scalable data workflows across secure cloud and on-premise environments
- Combine structured, unstructured, and geospatial data to build models and extract actionable insights
- Apply statistical techniques, machine learning, and AI to solve domain-specific problems
- Collaborate with engineers, analysts, and stakeholders to develop robust data-driven solutions
- Support the optimisation and maintenance of data pipelines, storage systems, and performance processes
Key Requirements:
- 6+ years’ experience working in a Data Scientist role or similar
- Strong programming skills in Python, with knowledge of SQL and data visualisation tools (e.g. Tableau or Power BI)
- Solid understanding of statistics, mathematics, and machine learning fundamentals
- Experience working with large datasets and contributing to analytical platforms or data products
If you\’re a Data Scientist looking to step into a role with real purpose and long-term opportunity, and want to be part of a growing function working on work that matters, please get in touch.
Seniority level
-
Seniority level
Mid-Senior level
Employment type
-
Employment type
Full-time
Job function
-
Job function
Design, Engineering, and Management
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Industries
IT Services and IT Consulting, Security and Investigations, and Military and International Affairs
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Senior Data Scientist employer: developrec
Contact Detail:
developrec Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, SQL, and data visualisation tools like Tableau or Power BI. Having hands-on experience with these will not only boost your confidence but also demonstrate your readiness for the role.
✨Tip Number 2
Showcase your experience with large datasets and analytical platforms by preparing examples of past projects where you successfully applied machine learning techniques. Be ready to discuss these during any interviews to highlight your practical skills.
✨Tip Number 3
Network with professionals in the data science field, especially those who work in geospatial data or similar sectors. Engaging with them can provide insights into the company culture and expectations, which can be invaluable during your application process.
✨Tip Number 4
Prepare to discuss how you approach problem-solving in a collaborative environment. Since the role involves working with engineers and stakeholders, demonstrating your ability to communicate complex ideas clearly will set you apart from other candidates.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in data science, particularly your programming skills in Python and any work with SQL or data visualisation tools. Use specific examples to demonstrate your expertise in handling large datasets and applying statistical techniques.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your background aligns with their needs, especially your experience with geospatial data and machine learning. Be sure to convey your passion for solving real-world challenges through data.
Showcase Relevant Projects: If you have worked on projects that involved designing data workflows or building models, include these in your application. Briefly describe the challenges you faced, the solutions you implemented, and the impact of your work.
Highlight Soft Skills: Data scientists often collaborate with various teams. Emphasise your communication and teamwork skills in your application. Mention any experience you have working with engineers, analysts, or stakeholders to develop data-driven solutions.
How to prepare for a job interview at developrec
✨Showcase Your Technical Skills
As a Senior Data Scientist, you'll need to demonstrate your strong programming skills in Python and familiarity with SQL. Be prepared to discuss specific projects where you've applied these skills, and consider bringing along a portfolio of your work or relevant case studies.
✨Understand the Business Context
It's crucial to understand how data science can solve real-world problems for both public and private sectors. Research the company’s recent projects and be ready to discuss how your expertise can contribute to their goals, especially in geospatial data and analytics.
✨Prepare for Technical Questions
Expect to face technical questions related to statistics, machine learning, and data workflows. Brush up on key concepts and be ready to explain your thought process when solving domain-specific problems, as this will showcase your analytical thinking.
✨Emphasise Collaboration Skills
Collaboration is key in this role, so be prepared to discuss your experience working with engineers, analysts, and stakeholders. Share examples of how you’ve successfully collaborated on projects to develop robust data-driven solutions, highlighting your communication skills.
