Data Scientist

Role Overview: As a Data Scientist specializing in Generative AI & ML Engineering, your primary responsibility will be to research and develop AI algorithms and models. You will be tasked with analyzing data, constructing predictive models, and employing machine learning techniques to address intricate problems. Key Responsibilities: - Research and develop AI algorithms and models - Analyze data and construct predictive models - Employ machine learning techniques to address complex problems - Possess proficiency in languages/frameworks such as Fast API, Azure UI Search API (React), databases like Cosmos DB, and ETL tools such as Data Factory Data Bricks - Command of Python and R, familiarity with Azure Cloud Basics and Gitlab Pipeline - Experience in deploying AI solutions end-to-end - Expert-level knowledge in Azure Open AI, Open AI GPT Family of models, and Azure Storage Account - Expertise in machine learning algorithms, deep learning frameworks like TensorFlow and PyTorch - Solid foundation in mathematics including linear algebra, calculus, probability, and statistics - Proficiency in data analysis tools like Pandas, NumPy, and SQL - Strong statistical and probabilistic modeling skills - Experience with data visualization tools like Matplotlib, Seaborn, and Tableau - Knowledge of big data technologies like Spark and Hive Qualifications Required: - Proficiency in languages/frameworks such as Fast API, Azure UI Search API (React), Python, R - Experience with databases like Cosmos DB, ETL tools such as Data Factory Data Bricks - Knowledge of Azure Cloud Basics, Gitlab Pipeline, Azure Open AI, Open AI GPT Family of models, Azure Storage Account - Expertise in machine learning algorithms, deep learning frameworks like TensorFlow and PyTorch - Strong foundation in mathematics including linear algebra, calculus, probability, and statistics - Familiarity with data analysis tools like Pandas, NumPy, SQL, and data visualization tools like Matplotlib, Seaborn, Tableau - Experience with big data technologies like Spark and Hive (Note: No additional details of the company were mentioned in the provided job description),