Data Scientist (Python)

About this role

• 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