Data Analytics Scientist (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 5+ years of proven experience in data science, data engineering or quantitative analytics
• Proficiency in writing structured and efficient SQL queries for large data sets
• Expertise in statistical analysis, including hypothesis testing, experimentation using statistical software packages in Python, R, or equivalent
• 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 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 organized, good planner, able to work independently and meet deadlines
• Previously experience in a fraud, risk & payment management environment is an advantage

ABOUT THE ROLE:

Billie’s Analytics team is at the heart of the company supporting multiple functions to make data-driven decisions. The Analytics team works closely with all Product segments, and other departments by innovating, hypothesizing, strategizing and providing recommended actions to relevant stakeholders (Decision Science, Business Development and Account Management, Collection and Underwriting teams, Customer support and Marketing) in an integrated, scalable, secure and compliant way to enable the company’s sustainable growth.
We are looking for a Data Scientist to join Billie’s Analytics team and contribute to the development and enhancement of Billie’s analytical capabilities.
In this role, you will have the chance to make a significant impact by leveraging data and analytics tools, will look for solutions, establish relationships to be able to guide business decisions within the company values and expectations, and contribute to the ongoing growth of our portfolio.
As a Data Scientist at Billie, your role involves diving into our data to solve crucial business problems. The scope of this role ranges from diagnosing problem areas to identifying solutions to designing experiments and ultimately influencing decision-making. This is a rare, operational and actionable data-driven experience that requires a good mix of technical and stakeholder engagement skills. As part of the Analytics team, you will be driving action from the frontlines, owning the business outcome, rather than just doing yet another analytics or data science role.
This is a unique opportunity for data scientists who are eager to immerse themselves in the heart of the fintech business, develop additional muscles, and grow within a fast-paced and dynamic environment. You will collaborate with cross-functional teams, apply creative problem-solving skills, and drive business growth through data-driven strategies.

WHAT WILL YOU DO?

• Perform analysis to develop a deep understanding of the product, and its usage, business processes, and to support business and research hypotheses, including A/B testing of product ideas, identifying new product and business opportunities
• Find patterns in huge amounts of data
• Support product segments in asking the right questions and creating efficient solutions that deliver positive results
• Design data models as part of data solution to support reporting and analysis needs
• Perform comprehensive data analysis and EDA to support Risk and Fraud systems optimization
• Build ML models to solve real business problems, and work closely with MLOps and Engineering teams to bring them live
• Communicate and present recommendations and key insights to stakeholders and executives to drive business decisions and create an impact
• Communicate issues in an independent and timely manner with appropriate internal and external partners