Beat is one of the most exciting companies to ever come out of the ride-hailing space. One city at a time, all across the globe we make transportation affordable, convenient, and safe for everyone. We also help hundreds of thousands of people earn extra income as drivers.
Today we are the fastest-growing ride-hailing service in Latin America. But serving millions of rides every day pales in comparison to what lies ahead. Our plans for expansion are limitless. Our stellar engineering team operates across a number of European capitals where, right now, some of the world’s most ambitious and talented engineers are changing how cities will move in the future.
Beat is currently available in Greece, Peru, Chile, Colombia, Mexico and Argentina.
About the role
You enjoy raising the bar, all the time. You are interested in the ride-sharing industry and how big an impact it builds in every part of the world, day by day. And that excites you because you never stop learning. As an Analytics Manager in Beat’s Fraud domain, you will manage a team and be an advocate of data to determine the best way to prevent and detect fraudulent activities within a plethora of different kinds of data. Your work on these to lead safer rides and transparent transactions, so as to ensure our products’ and services’ reliability and trustworthiness.
You will find a stimulating environment where you will work along with spectacular colleagues on exciting projects that deliver real business outcomes in the most exciting industry in the world! You will play a key role in building, leading, and analysing data to search for patterns and connections that will be translated into important business strategies. Your impact will be truly global as you will work in a diverse team with the goal to grow Beat business and improve the experience for both riders and drivers.
What you’ll do day in day out:
- Supervise, analyse, visualise and communicate key metrics to management
- Support the continuous improvement of our reporting framework, suggest new perspectives and educate business partners
- Conduct insightful analysis using a multitude of data points (e.g. user, device, events, revenue, coordinates, …)
- Manage a team and be the point of contact on fraud and safety matters when it comes to data.
- Collaborate closely with fellow analysts and senior partners to drive informed business decisions
- Work closely with different teams (Engineering, Product, Operations) to assess and improve current business processes. Advocate for a data-driven culture across the organisation.
- Analyse Fraud and Cyber patterns, dig deep to find the data you need to identify fraudsters, and measure the accuracy of your detection and prevention. Challenge analyses of peers and reports. Also, suggest implementations of new features for fraud detection and prevention to the product team, while deploying new workflows (python), when applicable, to impact the business directly.
- Think about automation and design workflows that contribute to increased accuracy in fraud prevention while reducing the volume of manual reviews
- Layout the foundations of the data cockpit on which machine learning efforts will take place
What you need to have:
- 5 year’s of proven experience in a quantitative or analytical role in a dynamic, constantly evolving environment
- Exceptional knowledge in SQL and databases
- Experience in R and/or Python
- Be the key driver to advocate data-driven decision making
- Communicate to all levels from people in the field to senior partners.
- Leading a team of data analysts to develop their fraud knowledge mindset and increase the impact of their work.
- Previous experience in establishing a team is advantageous.
- Bachelor’s and/or Master’s Degree in Economics, Maths, Electrical engineering Computer Science, Statistics or other quantitative fields
- Proficiency in creating data products, complex interactive dashboards, reports and custom solutions
- Strong analytical skills, problem-solving approach, and business acumen
- Hands-on experience in using leading data visualization tools (preferably Tableau) for producing engaging and useful insights
- Ability to collaborate with individuals from varying backgrounds and skillsets
- Excellent multitasking skills to lead multiple projects across various teams and topics
What’s nice to have:
- Familiarity with the fraud domain and anomaly detection
- Worked on Risk, Security and Safety projects previously
- Experience in feature engineering
- Exposure and collaboration around Machine Learning is highly desirable
What’s in it for you:
- Competitive full-time salary
- Flexible working hours, top Line tools, Spanish Lessons
- Working in a hyper-growth environment, you will enjoy numerous learning and career development opportunities
- Breakfast, high-quality daily lunch on a very low cost, fruit and snacks all day long
- Commuter Benefits Program
- Bonding Benefit
- Pension Benefit
- A great opportunity to grow and work with the most amazing people in the industry
- Being part of an environment that offers challenging goals, autonomy and mentoring, which creates incredible opportunities, both for you and the company.