At a Glance
- Tasks: Lead a team of analysts to optimise customer acquisition and engagement.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, diverse team culture, and opportunities for professional growth.
- Other info: Inclusive environment celebrating diversity and empowering every team member.
- Why this job: Make a real impact on how the world manages money with innovative analytics.
- Qualifications: 4+ years in analytics, with leadership experience and strong analytical skills.
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. 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.
THE ROLE
We're looking for a Senior Product Analytics Manager to lead analytics for Scalable Growth Pod at Wise. You'll lead a team of 5 analysts in the teams, focusing on bringing high quality customers with low marketing cost, reporting into Onboarding and Scalable Growth Squad Analytics Lead. The Scalable Growth pod focuses on optimizing customer acquisition and engagement by strategically structuring its product engineering teams. The pod comprises several key areas including: Recommend, Organic Growth, and Marketing Platform. The pod aims to leverage data effectively to drive impactful initiatives and provide customers with compelling reasons to choose Wise, making robust analytical leadership crucial for achieving these objectives.
WHAT YOU'LL DO
- Partner with Product/Engineering/Design leads to identify opportunities to improve our product and bring them to life; review team plans and progress, giving them effective feedback.
- Create and communicate a clear picture of progress against product goals. Ensure that we have clear goals, measurable KPIs, narrate our progress and drive action to accelerate progress.
- Own data strategy for Scalable Growth Analytics: define the roadmap to build the data and tools necessary to scale impact.
- Increase the speed and effectiveness of decision making across the squad.
- Lead, develop and support a team of high performing analysts. Support analyst professional development via performance feedback & coaching; hire and plan capacity and ensure that analyst efforts maximise impact.
WHAT YOU'LL BRING
- 4+ years experience in analytics with 1+ years leading analysts.
- You have experience working with product teams: identifying and evaluating opportunities that will maximise impact for customers and KPI progress; evaluating the impact of what you shipped; recommending changes and new initiatives.
- Analytical thinker with strong analysis skills (SQL, Python), data modelling (e.g. airflow, dbt) and experience using event data (e.g. Mixpanel).
- Hands-on experience designing and running experiments. You know how to design an experiment and analyse the data to get reliable insights, and you know your options when faced with limitations like small sample sizes or short test duration.
- Bias to action: you identify what needs to be done and make it happen. You can work independently in a fast-paced environment (able to identify impactful projects and evaluate & triage inbound requests).
- Strong stakeholder management skills - you are collaborative, you know how to influence and when to say yes or no to maximise impact.
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.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Product Analytics Manager - Scalable Growth 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 Senior Product Analytics Manager - Scalable Growth 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 Senior Product Analytics Manager - Scalable Growth 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 Senior Product Analytics Manager - Scalable Growth 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.
