Credix is a FinTech company offering a Buy Now, Pay Later (BNPL) solution tailored for business-to-business (B2B) transactions in Brazil. Our platform empowers businesses to streamline their purchasing processes, improve cash flow management, and foster strong supplier relationships. As we expand in the Brazilian market, we seek a dynamic and experienced Machine Learning Engineer to join our Risk&Data team.
Learn more about our team, culture, and vision on our company page.
Why choose Credix?
As we scale our presence in the Brazilian market, we are seeking an experienced Machine Learning Engineer. This person will be crucial in advancing our risk and fraud detection capabilities by developing, implementing, and deploying cutting-edge machine learning models. The ideal candidate will master both the theoretical aspects of machine learning and the practical engineering challenges, with a strong inclination towards rapid prototyping, testing, and iteration of data-driven solutions.
+5 years of experience as a data scientist and machine learning engineer
Fluent in English and Portuguese (written and verbal)
Strong background in developing, deploying, and monitoring machine learning models in production environments
Proven track record of applying machine learning models to assess credit risk and combat fraud in Brazil, focused on SMEs and ideally in the context of trade finance
Experience with data pipeline and workflow management tools (e.g., Apache Airflow)
Knowledge of cloud computing platforms (Google Cloud Platform) and their machine learning services
Familiarity with data storage and processing technologies (e.g., SQL, NoSQL, Hadoop, Spark)
Ability to work in a fast-paced, entrepreneurial environment, adapting to changing priorities and managing multiple projects simultaneously.
Analytical mindset, combined with outstanding interpersonal and communication skills
Design, implement, and deploy machine learning models to detect fraud and assess risk in real-time
Develop scalable data pipelines to ingest, clean, and process diverse datasets from various sources
Collaborate with the product and engineering teams to integrate machine learning models into the core product
Monitor and maintain the performance of machine learning models in production, making adjustments as necessary to ensure optimal operation
Conduct experiments, perform back tests and prototype new models to improve CrediPay's risk and fraud detection capabilities continuously
Unblock critical paths in the core product to enhance overall velocity and efficiency
Stay up to speed with the latest advancements in machine learning and data engineering, incorporating new technologies and methodologies to drive innovation
The opportunity to be part of a growing, international startup, directly impacting the company's strategy and growth.
A supportive, engaging, and dynamic work environment.
Competitive salary package: Your hard work deserves recognition, and we ensure you're well-rewarded for your contributions.
Equity stock options plan: Be a part of our journey towards success and share in the rewards.
Paid holidays: Enjoy the flexibility to recharge and rejuvenate.
Bi-annual off-sites: Awesome team building and adventures ensured during our team off-sites.
With access to our offices in either Sao Paulo or Antwerp, you'll immerse yourself in a culture of innovation and collaboration.