Data Enthusiast | Analytics & AI | M.Sc. Data Science

I'm a data science graduate student based in Berlin, passionate about solving real-world problems using data and AI. My work spans across:

• 📊 Data Analytics & Business Intelligence
• ⚙️ End-to-end Machine Learning Pipelines (Airflow, Docker)
• 🤖 Large Language Models (LLMs) & Retrieval-Augmented Generation
• 🧠 Data Engineering & Automation Workflows I’m fluent in English (C1) and speak intermediate German (B1). Currently open to internships and entry-level roles in Data Analytics and AI.

• Developed a cricket match summarization system from commentary using Large Language Models.
• Fine-tuned LLaMA-2 with LoRA/QLoRA on 400k+ lines IPL commentary. Implemented factual guardrails and evaluated with ROUGE, F1 Score and Human Reviews.
• Achieved >95% factual accuracy enabling automation of human-like post-match summaries.

• This end‑to‑end case study dives into a marketing dataset to answer business questions such as which channels generate the most profit relative to ad spend, how valuable customers are over time and whether marketing spend is efficient
• Instead of stopping at exploration, the project adds simulated business context, computes KPIs (CLTV, ROI, CAC & Churn) and segments customers by channel, income and behaviour
• It demonstrates business‑focused analytics and data storytelling. Python, pandas, seaborn, matplotlib

• The project loads and cleans data in PostgreSQL, extracts actionable insights through SQL queries and visualises the results, then summarises findings for business relevance

• Developed a retrieval‑augmented generation pipeline using Hugging Face, FAISS and LLaMA 2 to summarise cricket matches.
• Cleaned and aligned 500 k+ texts and evaluated outputs for coherence and quality.

• Built and deployed an ML pipeline using Airflow and Docker to automate data ingestion, pre‑processing and model retraining.
• Reduced manual maintenance by 80 %.

1. Team‑player & fast learner
2. Analytical rigour and attention to detail
3. Curiosity and problem‑solving mindset
4. Structured organiser

• Master’s in Data Science – University of Europe for Applied Sciences, Berlin (Sept 2023 – August 2025)
• B.Sc. Computer Science – University of Pune, India (Jul 2019 – Sept 2022)

1. AWS Cloud Foundations (2024)
2. BCG GenAI Job Simulation on Forage (2025)
3. Python for Data Science 101 (2022)
4. KNIME Analytics Platform L1 (2024)