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