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- Tasks: Transform data into actionable insights and support innovative projects.
- Company: Join Camlin, a global tech leader revolutionising industries.
- Benefits: Competitive salary, flexible work options, and growth opportunities.
- Other info: Collaborative environment with a focus on innovation and quality.
- Why this job: Make a real impact by solving complex data challenges.
- Qualifications: Strong analytical skills and proficiency in SQL and data tools.
The predicted salary is between 30000 - 40000 ÂŁ per year.
Camlin is a global technology leader that operates with the vision of bringing revolutionary products to life for a wide range of industries, including power and rail, and also has interests in a number of R&D projects in a variety of scientific sectors. At Camlin we believe in high quality engineering and design, allowing us to develop market‑leading products and services. In short, we love creating value for our customers by solving difficult problems. As of now, Camlin operates in over 20 countries worldwide.
As a Data Analyst, you play a critical role in converting data into actionable insights that fuel innovation, strengthen operational decision‑making, and accelerate delivery. Supporting the Data & Delivery Lead, you will perform high‑quality analysis, build reliable datasets, and contribute to the shaping, validation, and monitoring of data solutions. Your work ensures accuracy, clarity, and integrity across the entire delivery pipeline.
Responsibilities- Data Analysis & Insight Development
- Exploratory Analytics: Conduct detailed exploratory data analysis to identify trends, root causes, and opportunities for improvement or innovation.
- Hypothesis Testing: Support early‑stage discovery by testing hypotheses and validating assumptions through rigorous quantitative analysis.
- Insight Packaging: Translate complex findings into clear, concise insights, visualisations, and recommendations for both technical and non‑technical stakeholders.
- Data Wrangling: Prepare, clean, and transform datasets to support modelling, prototyping, and production‑ready pipelines.
- Requirements Translation: Work with the Data & Delivery Lead to convert exploratory findings into structured, well‑defined data requirements for engineering teams.
- Pipeline Validation: Assist in user acceptance testing, data validation, and quality assurance for new or enhanced data pipelines.
- Quality Checks: Perform ongoing data profiling, validation, and anomaly detection to ensure data flowing into solutions is accurate, complete, and reliable.
- Issue Investigation: Identify data issues at source or within pipelines and collaborate with the Data & Delivery Lead and source owners to support remediation.
- Documentation: Maintain clear, accurate data dictionaries, lineage notes, and quality logs to support compliant, traceable data practices.
- Work Intake Preparation: Assist with initial scoping, data feasibility assessments, and effort estimation for incoming work.
- Cross‑Team Coordination: Work closely with Strategy & Foresight, Value Realisation, and Engineering to ensure a shared understanding of data requirements and deliverables.
- Monitoring: Support the configuration, maintenance, and reporting of data pipeline monitoring dashboards and alerts.
- Strong analytical experience working with complex datasets across multiple sources.
- Proficiency in SQL and modern data analysis tools (e.g., Python, R, Power BI, or equivalent).
- Experience preparing, validating, and documenting datasets for use in analytical models, dashboards, or production systems.
- Knowledge of data quality frameworks, data governance practices, and data cleansing techniques.
- Strong communication skills with an ability to translate technical detail into meaningful insights for business stakeholders.
- Comfortable working in agile delivery environments and collaborating with engineering teams.
Data & Discovery Analyst employer: Camlin Group
Contact Detail:
Camlin Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data & Discovery Analyst
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your analytical skills. Use real-life examples from your experience to demonstrate how you've tackled complex datasets and derived insights.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each application. Highlight your SQL and data analysis skills in your conversations, and show how you can add value to Camlin’s innovative projects.
✨Tip Number 4
Follow up after interviews with a thank-you note. It shows your enthusiasm for the role and keeps you fresh in their minds. Plus, it’s a great chance to reiterate why you’re the perfect fit for the Data & Discovery Analyst position!
We think you need these skills to ace Data & Discovery Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data & Discovery Analyst role. Highlight your analytical experience and any relevant tools you've used, like SQL or Python. We want to see how your skills match 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 analysis and how you can contribute to our mission at Camlin. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any projects that involved data analysis, make sure to mention them! Whether it's a personal project or something from a previous job, we want to see how you've applied your skills in real-world scenarios.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at Camlin!
How to prepare for a job interview at Camlin Group
✨Know Your Data Tools
Make sure you brush up on your SQL and any data analysis tools mentioned in the job description, like Python or Power BI. Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of the role.
✨Prepare for Hypothesis Testing Questions
Since the role involves hypothesis testing and exploratory analytics, think of examples where you've tested assumptions with data. Prepare to explain your thought process and the outcomes, as this will demonstrate your analytical skills and problem-solving abilities.
✨Translate Technical Jargon
Practice explaining complex data findings in simple terms. You might be asked to present insights to non-technical stakeholders, so being able to communicate clearly is key. Use examples from your experience where you successfully conveyed technical details to a broader audience.
✨Show Your Collaborative Spirit
The job requires working closely with various teams, so be prepared to discuss how you've collaborated in the past. Share specific instances where you coordinated with others to achieve a common goal, highlighting your teamwork and communication skills.