Job Description

in data science and machine learning methodologies,with experience in building models and getting them to production. Python (scikit-learn, pandas, seaborn, etc.) innotebooks and pure Python code for production, and strong proficiency in SQL. Knowledge of software development best practices,including testing, git, and code reviews, with experience in maintainingmodels. Experience working with Docker containers forreproducible data science workflows. Basic understanding of mathematical optimization isbeneficial. Experience with real time inference and streamprocessing is advantageous Soft skills: Strong hands-on data hypothesis testing skills,with a solution-focused mindset. Ability to critically analysis data approaches,assumptions, and solutions to improve processes and outcomes. Preference for simple, effective solutions,particularly in technical model development and deployment. Expertise in agile environments with strongcollaborative skills, working closely with cross-functional teams. Clear communication of statistical and machinelearning concepts to technical audiences.

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