Roles and Responsibilities

• Support and maintain existing data science models, ensuring they remain up-to-date and functioning properly.
• Run basic experiments, tests, and diagnostics on managed ML platforms (e.g., Datarobot) to validate and improve models.
• Work with data sources (e.g., Tableau) and translate calculations into scalable solutions using SQL and Python.
• Collaborate with data scientists and engineers to improve and refine existing systems and processes.
• Use ML platforms (e.g., Datarobot) and work with cloud-based tools to support development, training, and deployment of models.
• Develop, write, and document code for automation, model training, and other tasks related to data science workflows.

Skills & Qualifications

• Strong background in Python, SQL, and working with data models and processing.
• Understanding of basic ML/DS concepts, algorithms, and workflows. Experience with ML model training, validation, and experimentation.
• Ability to understand Tableau data sources and translate its calculations into production-ready code (SQL and Python).
• Hands-on experience with ML platforms (e.g., Datarobot) for managing, deploying, and testing models.
• Advanced proficiency in Python, including working with libraries such as Pandas, NumPy, and scikit-learn.
• Solid SQL skills for querying and transforming data, particularly for integration with Tableau and other data sources.
• Familiarity with Large Language Models, even if not a primary focus.
• Experience working in cloud environments such as AWS, Azure, or GCP, and with cloud-based ML services.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 2+ years of hands-on experience in a similar role with exposure to ML/DS models and data engineering.

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