Description
Position Summary, Responsibilities and Expectations: * Design, develop, and maintain machine learning models for use cases such as prediction, classification, and optimization * Build, optimize, and automate data pipelines using Python, PySpark, and SQL within Fabric and Snowflake environments * Perform exploratory data analysis (EDA) and feature engineering to improve model performance and interpretability * Deploy, monitor, and maintain production-level models to ensure scalability, reliability, and accuracy * Collaborate with business, product, and engineering teams to translate analytical insights into actionable solutions * Participate in AI and Large Language Model(LLM) initiatives, integrating language or generative models into workflows * Work with global, cross-functional teams across different time zones, requiring flexibility in working hours * Demonstrate a self-driven, proactive, and detail-oriented mindset, with strong ownership and adaptability in a fast-paced environment Essential Skills and Experience: * Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Finance, or a related field * Minimum 3+ years of hands-on experience in data science, analytics, or machine learning roles * Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and solid understanding of machine learning workflows * Experience with SQL and PySpark for large-scale data processing * Familiarity with modern data platforms such as Snowflake and Fabric * Experience with Git-based version control systems (e.g., GitHub or Bitbucket) * Knowledge of AI applications, including prompt-based systems and exposure to Large Language Models (LLMs) * Strong English communication skills, with the ability to collaborate effectively with global teams and present insights clearly * Ability to work flexible hours to support collaboration across different time zones This role is intended for a Mid-Senior Data Scientist, responsible for driving data-driven decision-making and improving operational efficiency through advanced analytics and machine learning techniques. The position involves designing and applying machine learning models on large-scale, global datasets, while contributing to scalable AI solutions, including emerging applications in artificial intelligence(AI) and large language models(LLMs). It also requires close collaboration with cross-functional, international teams to translate data insights into business value using modern data platforms and technologies.