At a Glance
- Tasks: Help a fashion retail client clarify their messy inventory data across multiple spreadsheets.
- Company: Join a dynamic team supporting a PE-backed fashion retail client.
- Benefits: Enjoy hybrid working, flexible hours, and a quick interview process.
- Other info: Fashion retail experience is a bonus; we value your analytical mindset!
- Why this job: Make a real impact by transforming chaotic data into clear insights.
- Qualifications: Experience with AI tools and strong communication skills are key.
The predicted salary is between 40000 - 50000 £ per year.
We're supporting a PE-backed fashion retail client on a freelance basis to help bring clarity to their inventory data. The client's inventory data currently sits across around ten different spreadsheets with no single agreed source of truth. We're looking for a sharp, personable Data Analyst to get under the hood, work directly with the client's team, and build a clean, centralised baseline of their current inventory position.
What you'll be doing:
- Working closely with client stakeholders to identify the source of truth across multiple spreadsheets
- Asking the right questions to untangle inconsistent, messy data
- Using Excel (and ideally AI tools) to build a clear, centralised view of inventory status
- Bringing structure and clarity - this is not a data engineering or system-building role
What we're looking for:
- Comfortable using AI tools to speed up data wrangling
- Confident, personable, and comfortable working with non-technical, client-side stakeholders
- Patient, low-ego, and happy to dig through messy spreadsheets to get to the answer
- Fashion retail experience is a bonus, not a must
The details:
- London-based, hybrid working - mainly remote
- Single-stage interview process - moving quickly, with slots available this week
Data Analyst employer: Remobi
As a Data Analyst with our PE-backed fashion retail client, you'll thrive in a dynamic and supportive environment that values clarity and collaboration. Enjoy the flexibility of hybrid working in London, where you can engage directly with stakeholders to make a tangible impact on inventory management. With opportunities for professional growth and a culture that encourages innovation, this role offers a rewarding experience for those looking to advance their career in data analysis.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst
✨Showcase Your Skills with a Public Portfolio
As a freelancer in data science, having a killer portfolio is essential. Showcase your projects on platforms like GitHub or create a personal website that details your work and techniques. This gives potential clients a clear picture of what you can do and helps you stand out from the competition.
✨Get Involved in Data Science Communities
Tap into online forums like Kaggle or Stack Overflow. Not only can you showcase your expertise, but you can also connect with other data scientists and potential clients. Plus, participating in competitions and discussions can elevate your profile in the field.
✨Leverage Local Networking Opportunities
Keep an eye out for local data science meetups or tech events in your area. These are golden opportunities to meet potential clients and collaborators face-to-face. Plus, who doesn't love a bit of networking over pizza and drinks?
✨Pitch Your Services Directly to Companies
Don't just wait for freelancing platforms to bring clients to you—be proactive! Research companies that could benefit from data science services and craft tailored pitches. Mention specific pain points you can address for them. Let’s get that freelance hustle going!
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Data Analyst at Remobi, it’s crucial to highlight your projects. Include a portfolio that features at least two or three projects involving data analysis, machine learning, or visualisation. Make sure to describe the tools and methodologies you used, so we can see your skills in action!
Quantify Your Achievements:Freelance gigs, especially in data science, often ask for proven results. In your CV, include any relevant metrics or outcomes from your previous work. Did your analysis help reduce costs by a certain percentage? Or did your predictive model improve performance? Numbers speak volumes!
Introduce Your Style:Since freelancing is all about your individual style and approach, use your cover letter to share how you tackle data problems. This is your chance to let us know how you think, your creative problem-solving methods, and how you would approach a project at Remobi.
Be Real About Your Rates:When you send in your application, don’t forget to mention your freelance rates and availability. We appreciate clarity up front, and it helps us gauge if you fit within our budget and timeline. Being transparent in this aspect shows professionalism and readiness!
How to prepare for a job interview at Remobi
✨Show Off Your Data Wizardry
As a freelancer in data science, you'll want to present a portfolio that showcases your best projects. We should pull together examples where you tackled real problems with data analytics, machine learning models, or visualisations. It's all about demonstrating your skills in action!
✨Be Ready to Dive Deep into Technical Questions
Expect to encounter some technical grilling during the interview. Prepare to discuss statistical methods, algorithms, or maybe even tackle a live coding challenge. We should brush up on tools like Python, R, or SQL—those are key players in the data science field. Don't just know them; be ready to explain your thought process!
✨Help Them Understand Your Work Style
Freelance gigs often mean you'll be working independently, so we need to convey our self-motivation and time management skills. Be prepared to talk about how you’ve handled multiple projects or met tight deadlines before. Sharing your approach to client communication can also give them confidence in your ability to deliver remotely.
✨Pitch Your Value Proposition
When freelancing, it’s crucial to clearly articulate what makes you unique. We should highlight not just technical skills but also the business impact of our projects. Think of a couple of stories where your data insights drove decision-making—this can be a game changer in showing why they should choose you for their freelance needs!
