Data Analyst (w/m/d)

at  Billie

We are Billie, the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. We are to create a new standard for business payments and have made it our mission to simplify the purchasing experience for all businesses making it a tool for growth. Our solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes and a highly scalable tech platform. This makes us a deep-tech company building financial products, not the other way around. We love building simple and elegant solutions and we strive for automation and scalability.

WHO WE ARE LOOKING FOR:

• You have at least 3-4 years proven experience in data analytics, data engineering or quantitative risk analytics
• You have excellent proficiency in SQL
• Proficiency in data and analytics concepts, tools, and methodologies
• Experience in designing KPI dashboards for all types of audiences up to C-level
• Proven track record of managing complex initiatives with strong emphasis on data, providing actionable insights and tracking success of those initiatives
• Able to communicate complex problems in a simple and relevant manner at all levels
• Experience with translating analytical insights into data driven business prioritization
• You are proficient in data visualization and analytics tools, like Tableau, Power BI, Looker
• You have strong business acumen coupled with highly analytical mindset
• You had the chance to work in a fast-paced and dynamic environment
• Strong sense of responsibility, self-starter, well organised, good planner, able to work independently and meet deadlines
• Excellent organization skills, and ability to manage multiple responsibilities
• Previously experience in a fraud, risk & payment management environment is an advantage

In light of rapidly evolving and scaling up its development trajectory, Billie has recently set up a Portfolio Risk Management function. The main objective is to measure, control and drive decisions to optimize one of the core business metrics - portfolio losses. In order to do so, the team manages risk by researching and innovating, strategizing and recommending risk mitigating actions to relevant stakeholders (Decision science, Business Development and Account Management, Collection and Underwriting teams) in an integrated, scalable, secure and compliant way to enable the company’s sustainable growth.
We are looking for a diligent Data (Risk) Analyst to join our Portfolio Management team and contribute to the development and enhancement of our portfolio risk management system.
In this role, you will look for solutions, establish relationships to be able to guide risk decisions within the company values and expectations and be able to mitigate risks while at the same time embrace growth opportunities.
The role is for someone who is a self-starter, enjoys exploring data for insights to support strategic decision making, is passionate about building data structures, analyzing and reporting on key performance indicators, comfortable to work on operational matters, willing to develop expertise in fraud and credit risk prevention, has excellent communication and strong interpersonal skills, is able to document effectively.

Responsibilities:

• Perform in-depth portfolio data analysis from various angles (credit risk, fraud, acceptance rate and funnel) to develop a deep understanding of business processes and product, and to support risk optimisation
• Design data models as part of data business warehouses to support reporting and analysis needs
• Create, maintain and update Portfolio management dashboards and reports using BI tools to communicate insights effectively
• Collect, consolidate, and closely track KPI metrics regarding portfolio performance, communicate key insights and recommendations to relevant stakeholders
• Perform in-depth data analysis to support Risk and Fraud systems optimization
• Identify and analyze potential sources of loss to minimize risk and estimate the potential financial consequences of a loss
• Connect all business stakeholders in order to present portfolio’s KPIs and drive the business approach to managing risk
• Communicate issues in an independent and timely manner with appropriate internal and external partners