At a Glance
- Tasks: Own end-to-end analytics projects and deliver impactful insights.
- Company: Fast-growing analytics specialist with a focus on data-driven businesses.
- Benefits: Remote-first work, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with variety and responsibility, perfect for those who thrive on impact.
- Why this job: Make a real impact by shaping client strategies through data analysis.
- Qualifications: Strong experience in data analysis, advanced SQL skills, and business understanding.
We're working with a fast growing analytics specialist working with modern, data-driven businesses to help them understand customers, improve performance, and make better decisions with data.
We're looking for a Senior Data Analyst / Analytics Engineer who enjoys owning work end to end and working across a variety of projects. This is a senior, hands-on role with real responsibility, real influence, and plenty of room to grow.
The role is an analytics engineering-focused position where you'll work closely with clients from day one. You'll typically run two projects at a time, each with clear scope, impact, and visibility.
You'll be responsible for:
- Gathering and shaping client requirements
- Building robust, well-structured data models using dbt
- Writing high-quality, performant SQL
- Delivering insights through BI tools
- Translating business questions into clear analytical outputs
- Managing stakeholders directly and owning delivery from start to finish
This is not a narrow reporting role. You'll see the full lifecycle of analytics work and have real input into how projects are delivered.
What we're looking for:
- Strong experience as a Data Analyst or Analytics Engineer
- Advanced SQL skills and dbt experience
- Confidence working end to end, from requirements through to insights
- Strong business understanding, not just technical execution
- Experience working with customer, product, marketing, or commercial data
- Bonus if you've had exposure to subscription or e-commerce businesses
This role suits someone who enjoys variety, responsibility, and impact, and who likes seeing their work used.
If that sounds like you, please apply below.
Senior Data Analyst in Oxford employer: Cognify Search
As a remote-first analytics specialist based in the UK, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to take ownership of their projects and drive meaningful change. With a strong focus on professional growth, we offer ample opportunities for skill development and career advancement, all while working with cutting-edge data technologies and collaborating closely with clients. Join us to be part of a forward-thinking team where your contributions are valued and have a direct impact on business success.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst in Oxford
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Cognify Search!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Cognify Search.
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We think you need these skills to ace Senior Data Analyst in Oxford
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Cognify Search, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cognify Search. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Cognify Search
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Cognify Search!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
