About Me
Professional
I am a Data Scientist with 5 years of experience building and deploying end-to-end AI solutions from concept to production. I specialize in Large Language Models (LLMs) including RAG with GPT-4 and generative AI pipelines, with a proven track record of business impact—reducing manual analysis by 40% and optimizing automated trading strategies. Highly skilled in Python, SQL, and cloud-native data science on GCP, Azure, and AWS.
Personal
When I’m not working, I spend my time traveling to new places, hiking through scenic trails, and hitting the gym 4 days a week to stay active and healthy. I’m always inspired by innovative ideas, and I enjoy researching new technologies to stay ahead in the field.
Education
M.S. Data Analytics, Concordia University St. Paul (GPA 3.91) — B.Sc., Nizam College (GPA 8.22)
Experience
Data Scientist
Piper Sandler, USA
Apr 2024 – Juli 2025
- Deployed GPT-4 + RAG research assistant cutting analyst turnaround time by 50% and accelerating insight generation.
- Built Neo4j knowledge graph + LLM retrieval layer enabling richer financial context extraction and fraud signal discovery.
- Prototyped autonomous trading / risk agents improving backtested risk-adjusted returns by 15% while informing production roadmap.
- Implemented graph + NLP fraud pipeline increasing precision by 20% and reducing manual review noise.
Graduate Research Assistant
Concordia University, St. Paul
Nov 2023 – Mar 2024
- Engineered retention model (Scikit-learn) achieving 88% accuracy informing student success interventions.
- Co-authored AI ethics grant proposal securing $50K in funding for responsible AI research.
- Performed large-scale social media NLP (SpaCy, NLTK) extracting sentiment + engagement drivers for strategic dashboards.
Data Scientist (Functioned as ML Engineer)
Infosys — Client: CVS Aetna (Healthcare)
Jun 2022 – Aug 2023
- Built patient segmentation (K-Means, DBSCAN) reducing 30-day readmissions by 12% for targeted interventions.
- Delivered cost & risk models (XGBoost/Random Forest on Vertex AI) reaching 85% accuracy for actuarial planning.
- Applied BERT for clinical entity extraction improving risk scoring and accelerating care gap closure.
- Generated compliant synthetic data (GANs) enabling privacy-preserving experimentation.
Data Scientist (Functioned as ML Engineer)
Infosys — Client: Charles Schwab (Financial Services)
Jun 2022 – Aug 2023
- Implemented agentic automation (ETL + anomaly detection) streamlining workflows and reducing manual oversight.
- Developed LLM chatbot prototypes + fine-tuning experiments to evaluate conversational servicing use cases.
- Optimized Databricks pipelines cutting processing time by 30% and improving availability of fraud signals.
- Applied ML for fraud and segmentation enhancing client risk stratification and retention strategies.
Data Analyst
Twilight Software Solutions, Hyderabad, India
Oct 2019 – Jun 2022
- Developed churn & demand forecasting models with robust data quality controls improving retention targeting.
- Applied statistical techniques + PCA to enhance signal-to-noise and model generalization.
- Engineered ETL pipelines and warehouses powering BI and executive KPIs.
- Built interactive Tableau dashboards accelerating decision cycles for stakeholders.
Skills
Core Stack
Python · SQL · Machine Learning · LLMs (RAG) · Spark · Cloud (GCP · Azure · AWS) · Databricks · Neo4j
Tech Stack
Featured Projects
ChatGPT NLP Analyzer
A sophisticated web-based NLP tool leveraging OpenAI's GPT-3.5 API for text analysis and processing.
Certifications
Machine Learning
Stanford University
Data Science & Cloud Computing
Infosys
Data Analytics
Cisco