At a Glance
- Tasks: Drive data-driven decisions and turn insights into actionable strategies.
- Company: Join a leading analytics team in a dynamic London-based environment.
- Benefits: Competitive salary, professional growth, and collaborative culture.
- Other info: Opportunity to work with diverse teams and tackle various business challenges.
- Why this job: Make a real impact by solving business challenges with data.
- Qualifications: Experience in data analysis, strong communication skills, and SQL expertise.
The predicted salary is between 40500 - 49500 £ per year.
We are looking for a Senior Data Analyst to join our data & analytics team. You will drive data-driven decision‑making across business functions by identifying strategic challenges, conducting in‑depth analysis and collaborating with stakeholders to turn data into actionable insights that support business objectives.
Responsibilities:
- Proactively identify strategic challenges where decision support anchored in data is needed.
- Drive data‑driven decision making in your initiative/product team by turning data into insights and providing clear, data‑driven recommendations.
- Apply advanced analytics methods and tools to model, execute and follow up initiatives from idea to industrialization.
- Own the full analysis process from problem and scope definition to data extraction, cleaning, analysis, visualization, recommendations, and presenting results.
- Turn business challenges into structured data analysis; define and set up measurable KPIs and OKRs and maintain their visualization for value reporting.
- Act as the data analytics expert in cross‑functional teams and collaborate with business stakeholders to solve business challenges using data analytics.
- Work on a broad variety of business challenges with a wide range of business stakeholders (sales, commercial, merchandising, etc.).
- Participate in the wider analytics community across the group.
Requirements:
- Proven several years of experience as either a Data Analyst, Product/Business Analyst or similar.
- Proven experience from sales, commercial, &/or merchandising business domain is a must.
- Have strong business sense and business interest with the ability of making sound interpretations of data and other information.
- Have excellent communication skills and are skilled in translating and explaining complex data analysis to non‑technical and/or senior stakeholders.
- Have hands‑on working experience writing advanced SQL queries to extract, prep, validate, and analyse large data sets.
- Have expert experience in Analytical tools i.e. Power BI.
- Have previous working experience or comfortable working cloud platform data analytics i.e. GCP – Big Query.
- Have skills in Microsoft Excel functions such as Power Pivot, Power Query, Tabular Editor, DAX etc.
- Are prestige less and enjoy collaborating with others to solve problems.
- Are fluent in English.
Senior Data Analyst - Merch employer: Aqilea (formerly Soltia)
Aqilea (formerly Soltia) is an attractive employer due to its focus on data-driven decision-making and the opportunity for employees to work on impactful projects. The collaborative work culture fosters professional growth and skill development in the field of data analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst - Merch
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We think you need these skills to ace Senior Data Analyst - Merch
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 Aqilea (formerly Soltia), 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 Aqilea (formerly Soltia). 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 Aqilea (formerly Soltia)
✨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 Aqilea (formerly Soltia)!
✨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.
