Staff Data Scientist
About the role:
The FinCrime(Financial Crime) team is committed to ensure Zepz is at the cutting edge of fighting bad actors in our space. We are a team of data scientists, machine learning engineers and software engineers that work together to go from ideation to production. We own end-to-end data engineering pipelines and ML models to the systems that serve predictions in real-time
What you will do:
Be the lead of our data science and advanced analytics initiatives across the FinCrime team
Constantly challenge our own assumptions in models - our “target audience” has a huge incentive to change their behavior to evade detection
Help shape what we build. Our current tech stack includes Airflow, Fivetran, DBT, Databricks and DynamoDB 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.
Extensive Industrial experience designing and productionising 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 (Databricks and Airflow are some of the platforms 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 organisation.
About the job
Apply for this position
Staff Data Scientist
About the role:
The FinCrime(Financial Crime) team is committed to ensure Zepz is at the cutting edge of fighting bad actors in our space. We are a team of data scientists, machine learning engineers and software engineers that work together to go from ideation to production. We own end-to-end data engineering pipelines and ML models to the systems that serve predictions in real-time
What you will do:
Be the lead of our data science and advanced analytics initiatives across the FinCrime team
Constantly challenge our own assumptions in models - our “target audience” has a huge incentive to change their behavior to evade detection
Help shape what we build. Our current tech stack includes Airflow, Fivetran, DBT, Databricks and DynamoDB 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.
Extensive Industrial experience designing and productionising 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 (Databricks and Airflow are some of the platforms 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 organisation.