Data Science Lead

Role & responsibilities As a Data Scientist, you will play a crucial role in analyzing complex data using statistical and machine learning models, providing valuable insights, and driving data-driven decision-making processes Analyze complex data using statistical and machine learning models to derive actionable insights Utilize Python for data analysis, visualization, and working with APIs, Linux OS, databases, big data technologies, and cloud services Develop innovative solutions for natural language processing and generative modeling tasks using NLP, Generative AI, and LLMs Collaborate with cross-functional teams to understand business requirements and translate them into data science solutions Work in an Agile framework, participating in sprint planning, daily stand-ups, and retrospectives Collaborate with cross-functional teams to understand business needs and translate them into analytical solutions. Research, develop and analyze computer vision algorithms in areas related to object detection, tracking, product identification and verification, scene understanding Ensure model robustness, model generalization, accuracy, testability, and efficiency Write product or system development code Design and maintain data pipelines and workflows within Azure Databricks for optimal performance and scalability. Communicate findings and insights effectively to stakeholders reports and visualizations. Preferred candidate profile A Master's degree in Data Science, Statistics, Computer Science, or a related field. Over 5 years of proven experience in developing machine learning models, particularly for time series data within a financial context. Advanced programming skills in Python or R, with extensive experience in libraries such as Pandas, NumPy, and Scikit-learn. Comprehensive knowledge of AI and LLM technologies, with a track record of developing applications and models. Proficiency in data visualization tools, such as Tableau, Power BI, or similar platforms. Exceptional analytical and problem-solving abilities, coupled with meticulous attention to detail. Superior communication skills, enabling the clear and concise presentation of complex findings. Extensive experience in Azure Databricks for data processing, model training, and deployment. Proficiency with Azure Data Lake and Azure SQL Database for data storage and management. Experience with Azure Machine Learning for model deployment and monitoring. In-depth understanding of Azure services and tools for data integration and orchestration.