About DSG.AI

DSG.AI helps ensure the reliability and trustworthiness of scaled AI, Generative AI, and Intelligent Agents. As part of our mission, we address both the risks associated with AI and the development of innovative AI technologies, including machine learning and generative AI.

Summary

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.

Candidates will work on 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). Crucially, this position champions a "Vibe Coding" methodology, leveraging cutting-edge coding assistants (Cursor, Claude Code, VSCode Copilot, and Codex) to accelerate development cycles from ideation to production while maintaining high standards of reliability.

About the Role

As a Senior-Level Data Scientist at DSG.AI, you will:

• 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.
• Act as a technical leader in AI-assisted development, guiding the team in shifting from manual syntax generation to high-level, intent-based programming.

Key Responsibilities

• 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; implement RAG pipelines with embedding search and reranking.
• AI-Native Development & Vibe Coding: Utilize Vibe Coding workflows to rapidly prototype complex solutions using AI agents (Cursor, Claude Code). You will be responsible for "steering" AI code generation to ensure architectural soundness, security, and efficiency.
• Deployment & Monitoring: Wrap inference in RESTful APIs; set up MLOps workflows on Azure, AWS, or GCP; track data drift, latency, and cost metrics.
• Collaboration & Mentorship: Mentor junior data scientists on best practices for AI-augmented coding, conducting reviews to ensure AI-generated code meets production standards.

Tools & Technologies

• Languages & Frameworks: Python, SQL, scikit-learn, PyTorch.
• Cloud & MLOps: AWS SageMaker / Azure ML / GCP AI Platform / Docker (an advantage).
• AI Coding Assistants: Cursor, Claude Code, GitHub Copilot (Expertise required for Vibe Coding workflows).

Requirements

• Education: MSc or PhD in Computer Science, Information Systems, Data Science, or related field. (Must).
• Experience:
• 5–6 years in data science/ML roles with production deployments of both classical models and LLMs. (Must).
• Experience in leading small to medium-sized data science teams is an advantage.
• Skills:
• Vibe Coding / AI-Assisted Development (Demonstrated ability to use AI agents to 10x coding velocity).
• Statistical analysis and hypothesis testing.
• Prompt engineering, API development, and MLOps.

How to Apply

To apply, please submit your resume and cover letter outlining your relevant experience, qualifications, and your approach to AI-assisted workflows.

We thank all applicants for their interest; however, we will contact only those selected for an interview.