Senior Data Scientist

At least 5 years of professional experience as a data scientist Undergraduate or graduate degree in Computer Science, Engineering, Mathematics, or similar Excellent command in spoken and written English, at least C1 Expertise in ML algorithms and methods, especially in supervised learning, feature engineering and model evaluation Expertise in Python, especially SciKit Learn, Pandas, Numpy and other libraries used in building ML algorithms Very strong SQL skills and experience with Snowflake data warehouse Excellent communication skills and ability to engage with business partners Domain knowledge of venture capital, investment banking, finance or related fields Good understanding of software development best practices and CI/CD tools Hands on experience with DBT or SQL Mesh (extra points) Experience with Airflow and data connectors such as Polytomic, Fivetran etc. (extra points) Strong understanding of various data modeling techniques like Kimball Star Schema (extra points) Hands-on experience with building ML models in Snowflake (extra points) Good understanding of Docker (extra points)

Building, training, running and maintaining machine learning algorithms with Python Working with business and technical counterparts to refine models and present their performance Bringing own ideas and hypotheses to test and build models around in the scope of venture capital and investing Helping build and maintain data pipelines built with Python, Airflow and SQL Mesh on AWS and Snowflake Supporting data engineering team with maintenance of the system infrastructure on AWS and Snowflake