Are you a data scientist with strong programming skills and experience in design and implementation of ML pipelines? If you enjoy writing clean code, solving complex challenges and think at scale read on.

What would you work on?

As a data scientist with ML engineering specialization, you’re going to be responsible for:

• Developing advanced Data science solutions for problem statements in Finance.
• Designing and implementing modeling pipelines.
• Integrating manual experiments into automated pipelines and supporting other data scientists.
• Aiding continuous integration and development by leveraging cloud services (Azure).
• Setting up and demonstrating world-class standards and best practices in project execution and quality of delivery.
• Clearly communicating requirements, challenges, and solutions to other teams and stakeholders.

Our team focuses on cooperating closely with business-facing data science teams and providing them with custom tools as well as integrating their models into fully automatized, cloud deployed ML products. We work mainly on enterprise level solutions involving financial data.

We are looking for:

Passionate, self-motivated individual with previous experience in a similar position (Data Scientist/ML Engineer/Python Developer). You welcome challenges and can adapt quickly, always balancing the quality of your work with the timeliness of delivery.

Your strongest skills ideally are:

• Advanced Python programming and object-oriented software design
• Knowledge of classical ML techniques (emphasis on time-series forecasting), model evaluation, and underlying mathematics
• Experience using cloud services (Azure preferred)
• Use of container technologies like Docker and Kubernetes
• Git

Nice to have:

• Git repository to present your work.
• Skills in test-driven development.
• Experience with distributed computing.
• Understanding of CI/CD concepts and tools.
• Algorithm optimization.
• Understanding of finance/financial accounting.
• Ability to read and design UML documentation.