Senior Data Scientist

In today’s fast-evolving AI landscape, DSG.AI seeks a Senior-Level Data Scientist who excels in both classical machine learning and generative AI workflows. This ‘hands-on’ role will involve working on high-impact projects focused on both AI risk management and advanced AI development.

This role involves building end-to-end ML pipelines, covering data preprocessing, feature engineering, and model validation, as well as LLM-centric tasks such as prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG). The position also leverages cutting-edge coding assistants (Cursor, Windsurf, VSCode Copilot) to accelerate development and maintain high productivity. You will translate business requirements into robust ML and LLM solutions, ensuring both statistical rigor and generative quality, while prototyping, deploying, and monitoring models in production., * Classical ML: Develop regression, classification, clustering, and time-series forecasting models using scikit-learn, XGBoost, TensorFlow/PyTorch; conduct A/B tests and statistical analyses to validate performance

• Generative AI: Craft and refine prompts; fine-tune transformer models (e.g., GPT, LLaMA); implement RAG pipelines with embedding search and reranking
• Deployment & Monitoring: Wrap inference in RESTful APIs; set up MLOps workflows on AWS, Azure, or GCP; track data drift, latency, and cost metrics
• Collaboration & Mentorship: Integrate AI coding assistants into team workflows; mentor junior data scientists and conduct code reviews to uphold best practices
• Translate business requirements into robust ML and LLM solutions, ensuring both statistical rigor and generative quality
• Prototype, deploy, and monitor models in production, partnering with data engineering and DevOps teams for seamless CI/CD integration

• Education: MSc or PhD in Computer Science, Information Systems, Data Science, or related field
• Experience: 5-6 years in data science/ML roles with production deployments of both classical models and LLMs - a must
• Experience in leading small to medium-sized data science teams is an advantage
• Skills: Statistical analysis, hypothesis testing, prompt engineering, API development, and MLOps
• Languages & Frameworks: Python, SQL, scikit-learn, TensorFlow, PyTorch
• Cloud & MLOps: AWS SageMaker, Azure ML, GCP AI Platform, Docker (an advantage)
• AI Coding Assistants: Experience with Cursor, Windsurf, GitHub Copilot in VS Code