At a Glance
- Tasks: Drive analytics for AI-powered search systems and deliver actionable insights.
- Company: Join a cutting-edge tech company focused on innovation and collaboration.
- Benefits: Enjoy flexible working, generous leave, private healthcare, and professional development support.
- Other info: Collaborative environment with opportunities for career growth and involvement in exciting projects.
- Why this job: Make a real impact on advanced data products and shape the future of search technology.
- Qualifications: Master's or PhD in Data Analytics or related field with strong SQL and Python skills.
The predicted salary is between 63000 - 77000 £ per year.
An exciting opportunity is available for a
Senior Data Analyst to drive analytics and evaluation for enterprise-scale search and AI-powered retrieval systems.
This role focuses on measuring search performance, developing experimentation frameworks, and delivering actionable insights that improve ranking quality, relevance, and user experience across advanced data products.
Working closely with data scientists, engineers, and product teams, you'll play a key role in shaping search evaluation strategies, optimizing AI-driven experiences, and enabling data-informed decision-making.
Key Responsibilities
- Lead analysis of search and retrieval system performance, including ranking quality and relevance.
- Define, standardize, and monitor search evaluation metrics such as NDCG, MAP, precision, recall, and CTR.
- Analyze user behaviour, query patterns, and content performance to identify optimization opportunities.
- Conduct in-depth analysis of ranking performance, query intent, and retrieval gaps.
- Support evaluation of AI-powered and retrieval-based applications.
- Design and lead A/B testing frameworks, ensuring statistical accuracy and meaningful experimentation.
- Partner with Product, Engineering, and Data Science teams to define success metrics and experiment strategies.
- Build scalable analytics workflows and reusable reporting templates.
- Develop dashboards and visualizations that track search performance and user engagement.
- Deliver clear, data-driven insights to both technical and non-technical stakeholders.
- Work with large-scale datasets using modern data platforms while maintaining high standards for data quality and measurement consistency.
- Collaborate with engineering teams to improve data collection, logging, and observability.
- Act as a trusted analytics partner across cross-functional teams and contribute to the continuous improvement of search evaluation practices.
Requirements
- Master's degree or Ph D in Data Analytics, Statistics, Computer Science, or a related field (or equivalent practical experience).
- Significant experience in data analytics, business intelligence, or similar analytical roles.
- Strong proficiency in SQL and Python for large-scale data analysis.
- Advanced experience with business intelligence and data visualization tools such as Tableau, Power BI, Looker, or similar.
- Experience working with Databricks, Spark, or comparable large-scale data platforms.
- Strong understanding of experimental design, A/B testing, and statistical analysis.
- Experience measuring search and retrieval performance using metrics such as NDCG, recall, precision, and ranking metrics.
- Ability to translate complex analytical findings into clear business recommendations.
- Excellent communication and stakeholder management skills.
- Preferred Experience
- Experience with search, ranking, recommendation, or information retrieval systems.
- Knowledge of indexing, ranking algorithms, and query understanding.
- Experience working with clickstream data and user behaviour analytics.
- Exposure to machine learning evaluation frameworks.
- Familiarity with Retrieval-Augmented Generation (RAG) systems and Generative AI applications.
- Flexible and hybrid working options.
- Generous annual leave with the option to purchase additional leave.
- Private healthcare and wellbeing support.
- Pension scheme and life assurance.
- Share incentive programmes.
- Family-friendly leave policies.
- Professional development and study support.
- Volunteer leave and charity initiatives.
- Employee wellbeing programmes and additional lifestyle benefits.
This is an excellent opportunity for an experienced data professional looking to influence the performance of cutting-edge search and AI technologies while working on complex, high-impact analytical challenges within a collaborative, innovation-driven environment.
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Senior Data Analyst employer: SoTalent
SoTalent is an exceptional employer that fosters a collaborative and innovative work culture, where engineers are empowered to push the boundaries of technology. Located in a vibrant tech hub, we offer competitive benefits, continuous learning opportunities, and a commitment to employee growth, making it an ideal place for those looking to make a meaningful impact in the field of software engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst
✨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 SoTalent!
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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 SoTalent.
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We think you need these skills to ace Senior Data Analyst
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 SoTalent, 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 SoTalent. 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 SoTalent
✨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 SoTalent!
✨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.