Description
We are seeking a highly skilled Sr. Data Scientist to join our team. As a Sr. Data Scientist, you will design, develop, and maintain machine learning models for use cases such as prediction, classification, and optimisation. You will build, optimise, and automate data pipelines using Python, PySpark, and SQL within Fabric and Snowflake environments. You will perform exploratory data analysis (EDA) and feature engineering to improve model performance and interpretability. You will deploy, monitor, and maintain production-level models to ensure scalability, reliability, and accuracy. You will collaborate with business, product, and engineering teams to translate analytical insights into actionable solutions. You will participate in AI and Large Language Model (LLM) initiatives, integrating language or generative models into workflows. You will work with global, cross-functional teams across different time zones, requiring flexibility in working hours. You will demonstrate a self-driven, proactive, and detail-oriented mindset, with strong ownership and adaptability in a fast-paced environment.
The ideal candidate will have a Master's degree in Data Science, Computer Science, Mathematics, Statistics, Finance, or a related field. They will have minimum 3+ years of hands-on experience in data science, analytics, or machine learning roles. They will have strong proficiency in Python (Pandas, NumPy, Scikit-learn) and solid understanding of machine learning workflows. They will have experience with SQL and PySpark for large-scale data processing. They will have familiarity with modern data platforms such as Snowflake and Fabric. They will have experience with Git-based version control systems (e.g., GitHub or Bitbucket). They will have knowledge of AI applications, including prompt-based systems and exposure to Large Language Models (LLMs). They will have strong English communication skills, with the ability to collaborate effectively with global teams and present insights clearly. They will have the ability to work flexible hours to support collaboration across different time zones.