Overview
We are Hiring Junior Data Scientist for Pune Location
Required Skills & Qualifications
● Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial
Intelligence, or a related quantitative fieldanalyticsvidhya.com (or equivalent practical
experience). A strong foundation in algorithms, statistics, and software engineering is
expected.
● Programming proficiency: Expert-level skills in Pythoncoursera.org, with hands-on
experience in machine learning and deep learning frameworks (PyTorch,
TensorFlow)analyticsvidhya.com. Comfortable writing production-quality code and using
version control, testing, and code review workflows.
● Generative model expertise: Demonstrated ability to build, fine-tune, and deploy largescale generative modelsanalyticsvidhya.com. Familiarity with transformer architectures
and generative techniques (LLMs, diffusion models,
GANs)analyticsvidhya.comanalyticsvidhya.com. Experience working with model
repositories and fine-tuning frameworks (Hugging Face, etc.).
● LLM and agent frameworks: Strong understanding of LLM-based systems and agentoriented AI patterns. Experience with frameworks like LangGraph/LangChain or similar
multi-agent platformsgyliu513.medium.com. Knowledge of agent communication
standards (e.g., MCP/Agent Protocol)gyliu513.medium.comblog.langchain.dev to enable
interoperability between AI agents.
● AI integration and MLOps: Experience integrating AI components with existing
systems via APIs and services. Proficiency in retrieval-augmented generation (RAG)
setups, vector databases, and prompt engineeringanalyticsvidhya.com. Familiarity with
machine learning deployment and MLOps tools (Docker, Kubernetes, MLflow, KServe,
etc.) for managing end-to-end automation and scalable workflowsanalyticsvidhya.com.
● Familiarity with GenAI tools: Hands-on experience with state-of-the-art GenAI models
and APIs (OpenAI GPT, Anthropic, Claude, etc.) and with popular libraries (Hugging
Face Transformers, LangChain, etc.). Awareness of the current GenAI tooling
ecosystem and best practices.
● Soft skills: Excellent problem-solving and analytical abilities. Strong communication and
teamwork skills to collaborate across data, engineering, and business teams. Attention
to detail and a quality-oriented mindset. (See Ideal Candidate below for more on
personal attributes.)