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