Senior Data Scientist

We are seeking a highly skilled Senior Data Scientist with expertise in Python, Machine Learning (ML), Natural Language Processing (NLP), Generative AI (GenAI), and Azure Cloud Services. The ideal candidate will be responsible for designing, developing, and deploying advanced AI/ML models to drive data-driven decision-making. This role requires strong analytical skills, proficiency in AI/ML technologies, and experience with cloud-based solutions.

Key Responsibilities:

• Design and develop ML, NLP, and GenAI models to solve complex business problems.
• Build, train, and optimize AI models using Python and relevant ML frameworks.
• Implement Azure AI/ML services for scalable deployment of models.
• Develop and integrate APIs for real-time model inference and decision-making.
• Work with large-scale data to extract insights and drive strategic initiatives.
• Collaborate with cross-functional teams, including Data Engineers, Software Engineers, and Product Teams, to integrate AI/ML solutions into applications.
• Implement CI/CD pipelines to automate model training, deployment, and monitoring.
• Ensure adherence to software engineering best practices and Agile methodologies in AI/ML projects.
• Stay updated on cutting-edge AI/ML advancements and continuously enhance models and algorithms.
• Conduct research on emerging AI/ML trends and contribute to the development of innovative solutions.
• Provide technical mentorship and guidance to junior data scientists.
• Optimize model performance and scalability in a production environment.

Required Skills & Qualifications:

• Proficiency in Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Hands-on experience in NLP techniques, including transformers, embeddings, and text processing.
• Expertise in Generative AI models (GPT, BERT, LLMs, etc.).
• Strong knowledge of Azure AI/ML services, including Azure Machine Learning, Azure Cognitive Services, and Azure Databricks.
• Experience in developing APIs for model deployment and integration.
• Familiarity with CI/CD pipelines for AI/ML models.
• Strong understanding of software engineering principles and best practices.
• Experience working in an Agile development environment.
• Excellent problem-solving skills and ability to work in a fast-paced, dynamic environment.
• Strong background in statistical analysis, data mining, and data visualization.

Preferred Qualifications:

• Experience in MLOps and automation of model lifecycle management.
• Knowledge of vector databases and retrieval-augmented generation (RAG) techniques.
• Exposure to big data processing frameworks (Spark, Hadoop).
• Strong ability to communicate complex ideas to technical and non-technical stakeholders.
• Experience with Graph Neural Networks (GNNs) and recommendation systems.
• Familiarity with AutoML frameworks and hyperparameter tuning strategies.