At a Glance
- Tasks: Analyse data to enhance user onboarding and account access experiences.
- Company: Join Wise, a global leader in money management and transfers.
- Benefits: Competitive salary, hybrid working, generous leave, and stock options.
- Other info: Diverse and inclusive team culture with excellent career growth opportunities.
- Why this job: Make a real impact on how people manage their money globally.
- Qualifications: Strong analytical skills, SQL expertise, and experience with data visualisation tools.
The predicted salary is between 75000 - 115000 £ per year.
hackajob is collaborating with Wise to connect them with exceptional professionals for this role. Please ensure you read the below overview and requirements for this employment opportunity completely.
Wise is a global technology company, building the best way to move and manage the world's money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere.
We're looking for a Lead Product Analyst (Individual Contributor) to join the Onboarding squad and the Account Access & Recovery team. The team owns key core flows helping guide users as they register, access and recover their Wise account. As a Lead Product Analyst, your mission will be to deeply understand the needs of our customers as they register to Wise for the first time and/or need to access their account, partner with your cross-functional team to solve the most critical pain points they are facing, drive strategy and growth by providing data driven insights and recommendations. This would mean finding the right balance and friction to deflect bad actors whilst providing legitimate users with a good experience. In this role, you will also have a unique opportunity to work across a horizontal team and collaborate with other domains like Onboarding, Fincrime, Finance, Product verticals and so on.
WHAT YOU'LL BE DOING:
- Derive actionable insights from data to inform product decisions, to help support and improve onboarding and access to Wise for new and existing customers.
- Partnering with your product manager, engineers and designers throughout the product development lifecycle to build and iterate product changes based on your insights.
- Evaluate high impact areas of opportunity, find ways to support & accelerate, or identify and advocate for better alternatives.
- Build automated data pipelines and dashboards to minimise repetitive tasks and allow data self-serve.
- Help your team understand their progress and communicate this outside of your team by defining and reporting on KPIs that measure what matters.
- Collaborate with cross functional teams to identify and prioritise opportunities for AI-driven automation and insight generation.
WHAT YOU'LL BRING:
- You have strong quantitative skills with hands-on data manipulation and analysis, advanced SQL skills and experience working with data pipelines.
- You have strong communication skills and an ability to translate business problems into analytical solutions.
- You have experience working with data visualisation tools (Looker, PowerBI, Tableau etc.) and Python/R.
- You have the ability to derive actionable insights from data to inform product decisions, from improving our onboarding flow to reducing friction and saving costs.
- Creative problem solving skills and an ability to prioritise in a fast-paced environment.
- Leverage AI tools and machine learning techniques to improve analytics outcomes and discover new, critical insights.
NICE TO HAVE BUT NOT ESSENTIAL:
- Knowledge of the FinTech ecosystem.
- Knowledge of the Fraud and Authentication space.
We believe teams are strongest when they are diverse, equitable and inclusive. We're proud to have a truly international team, and we celebrate our differences. 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.
What do we offer:
- Salary: £75,000 - £115,000.
- Company Restricted Stock Units.
- Numerous great benefits in our London office.
- 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.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Product Analyst - Onboarding in Bristol
✨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 Wise!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Product Analyst - Onboarding at Wise.
✨Leverage Professional Networks
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.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Product Analyst - Onboarding at Wise, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Product Analyst - Onboarding 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.
