Data Scientist (Python)

• Design, build, and deploy scalable production-ready solutions using Large Language Models (LLMs) for automation and advanced AI applications.
• Develop APIs and containerized web-based applications to integrate AI models into business workflows.
• Implement and manage LLMOps/MLOps pipelines for model deployment, monitoring, and lifecycle management.
• Set up automated workflows for model versioning, performance tracking, drift detection, and continuous evaluation against business KPIs.
• Integrate observability tools to enable real-time monitoring, system health checks, and compliance management.
• Develop and maintain data pipelines and CI/CD/CT workflows for model training, evaluation, and real-time inference.
• Analyze structured and unstructured data to generate insights and support strategic decision-making.
• Collaborate with software engineers, product managers, and business stakeholders to deliver end-to-end AI solutions.
• Communicate analytical findings and recommendations through reports, dashboards, and presentations.
• Work closely with UK-based teams to ensure smooth collaboration and alignment across time zones.

Required Skills & Abilities

• Strong programming expertise in Python with focus on clean, maintainable, and scalable code.
• Familiarity with web frameworks such as Flask, FastAPI, or Django.
• Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience with LLM fine-tuning, prompt engineering, and agent-based AI frameworks.
• Hands-on experience with modern GenAI frameworks such as LangGraph or LangChain.
• Strong expertise in data processing using Pandas, NumPy, and SQL.
• Experience working with large-scale data processing frameworks such as PySpark.
• Ability to translate complex business problems into scalable AI-driven solutions.
• Strong communication and collaboration skills, particularly when working with distributed teams.
• Ability to work in fast-paced environments while managing multiple projects simultaneously.

Qualifications & Experience

• Bachelor's or Master's Degree in Computer Science, Data Science, Statistics, or a related field.
• Minimum 3+ years of experience in software engineering, data science, machine learning, or AI engineering roles.
• Hands-on experience developing and deploying Generative AI / LLM applications in production environments.
• Experience implementing containerized deployments and CI/CD pipelines for AI applications.
• Exposure to cloud platforms such as Microsoft Azure and Databricks.
• Bonus: Experience working with large-scale datasets and distributed computing frameworks such as Apache Spark.

Originally posted on Himalayas