Data Scientist

Job Summary:
We are seeking a highly skilled and motivated Data Scientist to join our asset manager team. The Data Scientist will be responsible for developing, testing, and maintaining high-quality ML-based software applications using Python, Machine Learning libraries, Typescript, Web frameworks like React, and other relevant technologies. This role involves designing scalable solutions on AWS, supporting data-driven decision making, and integrating machine learning models with existing data pipelines.

Key Responsibilities:
ML Application Development: Develop, test, and maintain high-quality ML-based software applications using Python, Machine Learning libraries, Typescript, Web frameworks like React, and other relevant technologies.
Scalable Solutions: Design and implement scalable and efficient solutions on AWS, ensuring robust performance and security.
Data-Driven Decision Making: Support data-driven decision making by using Prefect for workflow orchestration and SQL, Snowflake for data warehousing.
Model Development: Develop and deploy machine learning models using Python and relevant libraries/frameworks.
Integration: Integrate machine learning solutions with existing data pipelines and DevOps practices.

Who You Are:
Passion for Data Science: You have a passion for data science and application development, thriving on innovation through the art of coding and storytelling.
Team Player: You are an excellent team player who collaborates effectively with both technical colleagues and business partners.
Hands-on Experience: You have hands-on experience with data science and machine learning techniques.

Minimum Qualifications:
Experience: 5+ years of Data Science with proficiency in Python and experience with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch).
Technical Experience: 2+ years of experience in Technical Python, AWS, and data analysis tools such as SQL and Pandas.
Preferred Qualifications:
Education: Bachelor's degree in Computer Science, Engineering, or a related field.
Additional Languages: Experience with other programming languages and frameworks.
CI/CD and DevOps: Knowledge of CI/CD pipelines and DevOps practices.
Data Engineering: Knowledge of data engineering practices and tools.
Agile Methodologies: Familiarity with Agile methodologies and project management tools.