At a Glance
- Tasks: Drive data-driven decisions to optimise operations and enhance customer experiences.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, inclusive culture, and opportunities for career growth.
- Other info: Be part of a diverse team committed to inclusivity and innovation.
- Why this job: Make a real impact on global finance while collaborating with diverse teams.
- Qualifications: Experience in data analysis and strong collaboration skills required.
The predicted salary is between 60000 - 80000 £ 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.
We’re looking for a Lead Data Analyst who is passionate about our mission of Money Without Borders to partner with our operational teams to help drive data-driven decisions that would support our fast-growing product through scaling and optimising the team. As a Lead Data Analyst, you'll be driving our analytics efforts in our operations teams, who do everything from supporting our customers when they need help, to screening for criminal activity, to verifying customer identities at scale. Most importantly, you’ll collaborate closely with your operational leads, product managers, designers and engineers to bring your insights into real change for our customers and help drive our mission.
Here’s how you’ll be contributing:
- Analytical Capacity Planning and Forecasting: Focus on building and refining analytical models for strategic capacity planning. Take ownership of forecasting efforts to align with business growth and operational demands.
- Data Pipeline Ownership: Take ownership of data pipelines to maintain and improve data flow, ensuring reliability and accuracy.
- Predictive Modeling and Cause and Effect Analysis: Develop and implement robust models to predict outcomes and perform cause and effect analysis to identify key drivers, optimise processes, and enhance decision‑making and strategic planning.
- Strategic Support and Analysis: Provide critical insights to assess the operational health of FinCrime function, conduct in‑depth cost analysis, and offer detailed analysis of operational metrics (including quality) to understand impacts on customer experiences.
- Performance Tracking and Initiative Optimisation: Monitor and track the performance of key strategic initiatives, capitalising on optimisation opportunities to enhance operational outcomes.
- KPI Implementation and Target Setting: Lead the development and implementation of the operations KPI tree and the target‑setting framework, integrating these within reporting pipelines and strategic operations.
- Stakeholder Collaboration and Process Standardisation: Collaborate closely with various stakeholders to standardise processes across forecasting, scheduling, and real‑time operations, promoting continuous improvement and strategic alignment.
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. 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.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs. Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Lead Analyst - FinCrime Operations employer: Wise
Wise is an exceptional employer that champions a diverse and inclusive work culture, empowering employees to contribute meaningfully to our mission of Money Without Borders. With a strong focus on professional growth, we offer robust career development opportunities and a collaborative environment where your insights can drive real change. Located in a vibrant city, our team enjoys the benefits of a dynamic workplace that values innovation and teamwork, making Wise a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Analyst - FinCrime Operations
✨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 Analyst - FinCrime Operations 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 Analyst - FinCrime Operations 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 Analyst - FinCrime Operations
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.
