At a Glance
- Tasks: Lead data analysis to enhance customer experience and streamline money transfers.
- Company: Wise, a global tech company revolutionising money management.
- Benefits: Hybrid working, generous leave, and stock options for all employees.
- Other info: Join an inclusive team dedicated to building money without borders.
- Why this job: Make a real impact in FinTech by improving customer journeys and trust.
- Qualifications: 5+ years in analytics, strong SQL & Python skills, and stakeholder management.
The predicted salary is between 70000 - 90000 £ per year.
Wise is a global technology company, building the best way to move and manage the world's money. As part of our team, you will be helping us create an entirely new network for the world's money. Your mission is to understand exactly what these customers need, pinpoint where their experience breaks down, and help the team focus on solving their most critical challenges. By bridging the gap between data and product strategy, you will make our product more predictable and build the trust required for customers to move significant capital with ease.
As a Lead Product Analyst within the Send tribe, you will provide the dedicated analytical capacity needed to drive our most critical workstreams, with a focus on:
- You will lead insight generation and impact tracking to improve how we verify transfers—specifically clarifying documentation requirements and removing friction from the process. You'll help us look around the corner to determine what the team should focus on next to make this journey seamless.
- You will analyze how we can improve our response times and service quality to ensure customers feel supported throughout their journey.
- You will help define the strategy for how we scale our support operations and identify which customer segments require more specialized attention to prevent churn.
Technical Skills: 5+ years experience in analytical roles with strong data analysis skills (SQL & Python). Experience conducting regular A/B tests and causal analyses to determine impact of product changes on defined metrics. Experience partnering with Product Managers and other Analysts to set KPIs and monitor the impact of new product features on conversion, stickiness and engagement.
Influence: Strong stakeholder management skills - you are collaborative, know how to influence and when to say yes or no to maximise impact. Experience delivering high quality data and self-serve analytics using tools like Airflow, dbt and Looker. Practically used + applied AI / machine learning techniques and built predictive models to get deeper insights. Knowledge of the FinTech ecosystem.
Additional Information: Company Restricted Stock Units. Numerous great benefits in our London office.
Key benefits:
- Hybrid working
- Paid annual holiday, sick days, parental leave and other leave opportunities
- 6 weeks of paid sabbatical after 4 years at Wise on top of annual leave
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Product Analyst - Send in Bristol
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
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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 Wise.
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We think you need these skills to ace Lead Product Analyst - Send in Bristol
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 Wise, 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 Wise. 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 Wise
✨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 Wise!
✨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.
