Lead Product Analyst

Lead Product Analyst

Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
hackajob

At a Glance

  • Tasks: Lead analytics efforts to combat financial crime and enhance customer experience.
  • Company: Join Wise, a global tech company revolutionising money management.
  • Benefits: Diverse team culture, competitive salary, and opportunities for career growth.
  • Other info: Collaborate with 300+ analysts and work on exciting cross-team projects.
  • Why this job: Make a real impact by using data to drive innovative solutions.
  • Qualifications: 5+ years in data analytics with strong SQL and Python 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. For everyone, everywhere.

We’re looking for a Lead Product Analyst to join the Financial Crime Platform team and partner with our Financial Crime and KYC Product teams to ensure we are making data-driven and innovative growth decisions while helping to combat financial crime. Financial Crime (Servicing) Platform is our internal risk infrastructure tool that unifies customer onboarding, identities and transaction monitoring controls, ensuring Wise is protected against financial crime and meets regulatory requirements and standards.

You will lead our analytics efforts in the Financial Crime Platform product team that balances the work between preventing financial crime and enabling a smooth customer experience. We work closely with our FinCrime teams in Fraud, AML, Sanctions, Verification… but we are a Platform team. Our work is to enable them, securely and fast.

This is a great opportunity for a Product Analyst that thrives solving technical challenges, or an Analytics Engineer that wants to be closer to business problems and product outcomes. You’ll also be part of a wider team of 300+ Analysts that you’ll get to collaborate with on cross-team projects, have knowledge sharing sessions and bring ideas on how we can improve analytics across Wise.

What You’ll Be Doing:

  • Collaborating with Product, Engineering and other Analysts to bring your insights into real change for our customers and help us work towards our mission.
  • You’ll expose the vast amounts of data available to our product teams in a meaningful and actionable way and support other teams in discovering insights in our data solutions.
  • Proactively contribute to, own, create, track key metrics and results for your product team, keeping them accountable and enthusiastic throughout the quarter.
  • Support senior and lead analysts by building pipelines, preparing reports, and visualisations.
  • Partner with data scientists and engineers to create new features for FinCrime prevention Machine Learning models and integrate with external vendors, and make our risk assessment models faster.
  • Building the framework for managing risk and customer experience.
  • Drive the discovery phase by scoping new opportunities and suggesting initiatives to reduce financial crime on Wise through meaningful insights.

Qualifications:

  • 5+ years of experience in data analytics.
  • 2+ years of experience in advanced analytics and statistical techniques.
  • You have extensive experience with SQL, dbt (ideally) and Python/R.
  • You have strong quantitative skills. Ideally a background in statistics, maths, physics, engineering, computing, or other scientific area.
  • Strong communication skills and an ability to translate business and engineering problems into analytical solutions while being sensitive to the customer’s needs.
  • You have an ability to structure business problems with minimal supervision and an ability to prioritise problems collaboratively with PMs and Engineers, as well as condense complex systems/ideas into simple-to-understand models.
  • Be proactive. You can take work beyond the analysis and get things done.
  • Your curiosity will drive you to discover novel insights from our unstructured datasets.
  • Hustler-mentality. You can take work beyond the analysis and get things done.
  • You have experience with data visualisation tools (Looker, PowerBI, Tableau etc.) and demonstrate storytelling ability with data.

Nice To Have But Not Essential:

  • Data Engineering/Data Science experience.
  • Experience with unstructured and big datasets.
  • Experience with user-facing products and data.
  • Experience in fincrime domain balancing risk and supporting customer experience.

Additional Information:

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 Product Analyst employer: hackajob

At hackajob, we pride ourselves on being an exceptional employer that fosters a culture of innovation and inclusivity. Our diverse team thrives in a high-performance environment where your contributions directly impact our multi-asset platform's success. With ample opportunities for professional growth and a commitment to employee development, joining us means being part of a forward-thinking company that values your expertise and ambition.

hackajob

Contact Details:

hackajob Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead Product Analyst

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We think you need these skills to ace Lead Product Analyst

Data Analytics
Advanced Analytics
Statistical Techniques
SQL
dbt
Python
R

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