Senior AI Data Scientist

Senior AI Data Scientist responsible for designing and building end-to-end large-scale AI/ML systems for forecasting, classification, regression, and predictive modeling. The ideal candidate will have deep expertise in building scalable solutions with proficiency in AI/ML frameworks, Python, SQL, data processing, distributed computing, and MLOps.
 
 Responsible for data ingestion and feature engineering to model development, deployment, and monitoring. Applying cutting-edge machine learning techniques and collaborating with cross-functional teams to develop impactful AI/ML solutions.
 
Responsibilities

• Develop and deploy scalable AI/ML pipelines for feature engineering, training, tuning, evaluation, and inference. 
• Leverage advanced time series analysis and classification techniques to enhance model precision and boost predictive performance. 
• Build efficient and scalable AI/ML models for real-time inference and batch processing.
• Collaborate with cross-functional teams to define AI/ML system requirements and integrate AI/ML models into business workflows. 
• Drive research and innovation by exploring new AI/ML techniques and incorporating the latest advancements in deep learning, transformers, LLMs, statistical modeling, and AI/ML algorithms. 
• Design and implement agent-based systems that combine machine learning, generative AI for decision-making, and workflow automation. 
• Develop intelligent agents capable of interacting with users and other systems to streamline operations, support dynamic content creation, and facilitate real-time problem solving. 
• Establish evaluation protocols for agent behaviors to ensure alignment with business objectives. 
• Foster open, respectful, and professional communication directly within the team, with co-workers/ teammates, and leaders across the organization.
• Develop ETL pipelines of data to be integrated with Azure Datalakes and Azure services.
• Performs other duties as assigned. 

Qualifications

• Master’s or Ph.D. in Computer Science, Data Science, Statistics, or a related field.
• 5 years of experience in data science or machine learning roles, with a strong portfolio of deployed AI solutions.
• Production-level experience with core quantitative analysis techniques (e.g., predictive modeling, machine learning, artificial intelligence, or natural language processing).
• Quantitative background with relevant experience using data to solve problems and answer questions
• Strong proficiency in Python, SQL, and experience with libraries/frameworks such as PyTorch, PySpark, and Tensorflow.

• Experience with MLOps tools and practices (e.g., MLflow, Azure DevOps, CI/CD for ML).
• Knowledge of relational and dimensional database structures, theories, principles, and practices.
• Familiarity with large language models (LLMs), generative AI, or deep learning.
• Strong knowledge of data architecture, data governance, and scalable data processing.
• Deep understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Hands-on experience with Azure Data Lake, Azure Machine Learning, and other Azure cloud services.