1000000 - 2300000 INR - Yearly
Pune, Maharashtra, India
Information Technology
Full-Time
CoffeeBeans
Overview
As an L1/L2 Data Scientist, you’ll work alongside experienced engineers and data scientists to solve real-world problems using machine learning (ML) and generative AI (GenAI). Beyond classical data science tasks, you’ll contribute to building and fine-tuning large language model (LLM)– based applications, such as chatbots, copilots, and automation workflows.
Key Responsibilities
Key Responsibilities
- Collaborate with business stakeholders to translate problem statements into data science tasks.
- Perform data collection, cleaning, feature engineering, and exploratory data analysis (EDA).
- Build and evaluate ML models using Python and libraries such as scikit-learn and XGBoost.
- Support the development of LLM-powered workflows like RAG (Retrieval-Augmented Generation), prompt engineering, and fine-tuning for use cases including summarization, Q&A, and task automation.
- Contribute to GenAI application development using frameworks like LangChain, OpenAI APIs, or similar ecosystems.
- Work with engineers to integrate models into applications, build/test APIs, and monitor performance post-deployment.
- Maintain reproducible notebooks, pipelines, and documentation for ML and LLM experiments.
- Stay updated on advancements in ML, NLP, and GenAI, and share insights with the team.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
- 2.5–5 years of experience in data science, ML, or AI (projects and internships included).
- Proficiency in Python with experience in libraries like pandas, NumPy, scikit-learn, and matplotlib.
- Basic exposure to LLMs (e.g., OpenAI, Cohere, Mistral, Hugging Face) or strong interest with the ability to learn quickly.
- Familiarity with SQL and structured data handling.
- Understanding of NLP fundamentals and vector-based retrieval techniques (a plus).
- Strong communication, problem-solving skills, and a proactive attitude.
- Experience with GenAI prototyping using LangChain, LlamaIndex, or similar frameworks.
- Knowledge of REST APIs and model integration into backend systems.
- Familiarity with cloud platforms (AWS/GCP/Azure), Docker, or Git.
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