At a Glance
- Tasks: Build scalable analytics tools and dashboards to drive data-informed decisions for sales teams.
- Company: Join Wise Business, a leader in international finance with a focus on growth.
- Benefits: Competitive salary, flexible working options, and opportunities for professional development.
- Other info: Dynamic role with opportunities to influence key business strategies.
- Why this job: Shape the future of business growth through impactful data insights and collaboration.
- Qualifications: Proficient in SQL and experienced in high-growth B2B tech environments.
The predicted salary is between 56700 - 69300 £ per year.
In this role you enable data-driven growth for Wise Business by building scalable analytics and tooling for frontline Sales Total Service teams. You will quantify and optimize portfolio performance, forecast outcomes, and drive revenue through data-informed GTM decisions. You’ll work cross-functionally to align marketing, analytics, and sales systems, delivering insights that scale with business growth. This is a chance to shape how Wise grows its international business account with measurable impact.
Responsibilities
- Build scalable self-serve dashboards, forecasting tools, and cohort health reports for AE and TS-AS teams; provide monthly leadership reports on performance and ROI.
- Monitor and improve portfolio performance for TS-AS and AE; drive strategies on forecast attainment, product activation, and churn prevention.
- Track and optimize Sales and TS-AS funnels; refine assignment criteria, assess channel performance, and diagnose blockers to revenue.
- Conduct TAM/SAM analyses and capacity/ramp-up forecasts to inform regional expansion and data-driven GTM transitions.
- Define KPIs for rep/agent health, SLA tracking, deal velocity, target attainment, and operational capacity.
- Partner with Marketing to optimize lead management and nurture journeys; collaborate with Analytics Engineering to establish single-source-of-truth data pipelines (including Salesforce integrations).
Key requirements
- Proficient in SQL and comfortable with data tooling (Snowflake, dbt, Git, Airflow, Python, Looker).
- Able to transform data into actionable insights and conduct opportunity sizing, forecasting, and scenario modeling.
- Experience in a high-growth B2B tech environment with close work to commercial teams.
- Solution-oriented with end-to-end project ownership and stakeholder negotiation skills.
- Excellent written and verbal communication with ability to document clearly and influence colleagues.
Lead Data Analyst - Wise Business - Commercial & Sales employer: Wise
Wise is an exceptional employer that fosters a culture of inclusivity and innovation, making it an ideal place for a Lead ML / Data Scientist to thrive. With a hybrid working model, generous personal development budgets, and a commitment to employee growth, you will have the flexibility and resources to excel in your role while contributing to meaningful projects that redefine how money moves globally.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Analyst - Wise Business - Commercial & Sales
✨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 Data Analyst - Wise Business - Commercial & Sales 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 Data Analyst - Wise Business - Commercial & Sales 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 Data Analyst - Wise Business - Commercial & Sales
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.
