About the role:

The Data Products team is committed to empower other Zepz teams to leverage data in order to solve analytical problems. We are a team of data scientists and machine learning engineers that work together to go from ideation to production. We own end-to-end data engineering pipelines and ML models that span multiple applications (think fraud detection, time series prediction of financial data, churn prediction and more).

What you will do:

• Help shape what we build. Our current tech stack includes Airflow, Fivetran, DBT, BigQuery and BigTable and is primarily in Python, leveraging some of the most used machine learning packages. You will build and maintain data pipelines and scalable machine learning inference systems in production.
• Own delivery. We’re driven by shipping value; you’ll own work beyond just a pull request. You’ll care about bugs, scalability, uptime and other non-functional requirements.
• Grow together. You’ll review other’s work and happily seek feedback on yours to ensure we build a better codebase and sharpen each other's skills. We believe in developing our people so you will be an important part of mentoring juniors in the team.
• Collaborate. You’ll be working closely with Product Owners, Data Scientists, Analysts and other Engineers to design and refine our work. We work as a team and your input will be key in many architectural decisions (some that you would own) and in driving consensus.

What you bring to the table: 

• You are a software engineer at heart, and you take pride in writing well-designed, robust, and maintainable code to solve problems. We understand code is read more than it’s written, and better off tested. Maintainability is a must.
• At least 3 years of industrial experience designing and productionizing ML systems.
• Solid understanding of Machine Learning fundamentals and ability to translate business requirements into machine learning solutions.
• Experience in statistical experiment design and performance analysis of machine learning models.
• Strong experience with Python, SQL and machine learning frameworks. Some data engineering experience is preferred (BigQuery, BigTable and Airflow are some of the tools we use, but any equivalent experience is appreciated).
• Excellent communication and presentation skills, with the ability to convey complex concepts to technical and non-technical stakeholders.
• Bias for action. You see a problem, you fix a problem. You get buy-in for your solutions and keep tickets moving. We’re always looking for ways to ship at pace.
• Opinionated. We want you to actively contribute to discussions and help build a shared understanding within the team and organization.