Data Scientist

Key Responsibilities

• Mine, process, and analyze web, product, sales, and digital marketing data at an event level.
• Utilize traditional machine learning techniques and language models (LLMs) to build great AI agents for different business needs.
• Assist in developing and optimizing LLM-driven solutions for tasks such as text summarization and basic customer support automation.
• Contribute to building and deploying predictive models and machine learning algorithms across customer profile and usage datasets.
• Support the deployment of machine learning models into production environments.
• Assist in designing and implementing basic model activation strategies and participating in A/B testing plans.
• Conduct evaluations of LLMs, focusing on basic performance metrics like accuracy and latency.
• Integrate LLM agents with APIs and assist in maintaining data models and improving taxonomy.

Key Skills

• Hands on experience with LLM models and basic knowledge of evaluation metrics for LLMs.
• Knowledge of designing and deploying agentic systems. knowledge bases, retrieval systems (RAG architecture), and orchestrating dynamic multi-agent workflows.
• Exposure to machine learning techniques including supervised and unsupervised learning
• Proficiency in Python, SciKit, SQL, Jupyter Notebooks and understanding of cloud platforms for data science tasks.
• Basic understanding of data mining and statistical analysis techniques.
• Continuous learner, keeping up-to-date with the latest advances in transformers, generative AI models, retrieval-augmented generation (RAG), and agentic AI frameworks.

Education and Experience

• B Tech or B. E. (Computer Science / Information Technology)
• 1+ years as a Data Scientist or similar roles.

Analytical and Personal skills

• Must have good logical reasoning and analytical skills.
• Good Communication skills in English – both written and verbal.
• Demonstrate Ownership and Accountability of their work.
• Attention to detail.