About
It is easy to lie with statistics. It is hard to tell the truth without it.
- Andrejs Dunkels
- Phone: +1 (571) 352-0572
- Location: San Francisco, CA
- Education: CMU Alumnus
- Email: nikhilreddyp29@gmail.com
I am a Carnegie Mellon University (CMU) alumnus, currently serving as a Senior Software Engineer at Microsoft. With over 5 years of industry experience in Machine Learning and Data Science, I specialize in building intelligent agentic systems and Knowledge Graph architectures.
My passion lies in developing sophisticated AI agents that can reason, learn, and adapt in complex environments. I create Retrieval-Augmented Generation (RAG) systems that integrate large language models with structured knowledge, enabling more accurate and contextually-aware AI applications. Through Knowledge Graphs, I build systems that understand relationships, infer connections, and provide intelligent recommendations beyond traditional machine learning approaches.
My journey is about transforming complex data into intelligent, autonomous systems that think, reason, and act in ways that mirror human intelligence while leveraging modern AI's computational power. I'm driven by building AI systems that not only process information but truly understand context and meaning.
Skills
Resume
Summary
Nikhil Reddy Pallepati
Armed with a solid foundation in Machine Learning from both academic and professional realms, my journey has been about turning data into impactful solutions. With a proven track record in deploying robust algorithms and optimizing models, I'm eager to contribute to innovative projects in my next professional chapter.
- San Francisco, CA
- (571) 352-0572
- nikhilreddyp29@gmail.com
Education
Master of Information Systems Management & Speciality: Business Intelligence and Data Analytics
August 2022 - August 2023
CARNEGIE MELLON UNIVERSITY (CMU), Pittsburgh, PA
Relevant Coursework: Machine Learning, Intermediate Statistics, Unstructured Data Analytics, Econometrics, Distributed Systems, Database Management, Time Series Forecasting, Managing Analytics Projects, Advanced Business Analytics, Agile Methodologies, Decision Making Under Uncertainity
Bachelor of Technology & Electronics and Communication
August 2014 - April 2018
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY (JNTUH), Hyderabad, India
Relevant Coursework: C Programming, Data Structures & C++, Object Oriented Programming in Java, Probability Theory and Stochastic Process, Computer Networks, Computer Organization
Professional Experience
Senior Software Engineer
January 2024 – Current
Microsoft, Redmond, WA
- Built a graph-based anomaly detection and ranking system over petabyte-scale telemetry, combined seasonality-adjusted z-scores, GraphSAGE embeddings with HDBSCAN, and VGAE reconstruction head to score and rank suspicious activity; an agentic LLM generated KG-grounded explanations for top-20 alerts in specific lookback window, improved analyst time-to-triage by over 40%.
- Developed transformer-based anomaly detection framework, leveraged Anomaly Transformer model and adaptive threshold to flag data drifts and pipeline anomalies across 300+ high-volume Azure datasets, boosting root cause analysis precision to 92%.
- Engineered and scaled 4+ petabyte-scale, fault-tolerant telemetry pipelines to empower Microsoft Security threat hunters in detecting and neutralizing attacker behaviors, improving incident traceability and protect Microsoft Azure at planet scale.
Sr. Software Engineer, Machine Learning
November 2023 – December 2023
PNC Financial Services, Pittsburgh, PA
- Developed and deployed LSTM-based model to analyze time-series data, classified transactions for 10,000+ customers. Accurately predicted credit risk behaviors, enabling collections team to strategically target outstanding balances and enhance recovery rates.
- Designed and implemented credit card scoring algorithms for business and consumer segments, utilizing LightGBM for machine learning model development and successfully integrated with FICO MLX platform to optimize decision-making processes.
- Performed comprehensive analysis on scoring models by querying data from Hadoop SQL platform, handling over 4 million records.
Machine Learning Engineer
May 2023 - August 2023
cPacket Networks (Capstone Project), Pittsburgh, PA
- Spearheaded design and deployment of Knowledge Graphs (KG) using community detection algorithms, resulting in enhanced anomaly classification and strategic pathway for future graph-based ML explorations
- Optimized the extraction, transformation, and load (ETL) process from cStor to KG and facilitated the extraction of complex network insights. This resulted in a 30-hour network downtime reduction, reflecting tangible increase in operational efficiency
Machine Learning Engineer
February 2019 - July 2022
Tata Consultancy Services - Digital (Analytics and Insights Team), Hyderabad, India, Client: Reserve Bank of India
- Built Natural Language Processing (NLP) model for automated product categorization from major E-commerce retailers, resulting in an 80% improvement in efficiency in calculating Consumer Price Index over time.
- Developed and deployed a Sentiment Analysis model, utilizing a dataset of 200,000 news articles to extract milestones discussed and overall polarity in news articles related to Reserve Bank Finance mentions.
- Designed, automated ticket prioritization of logged incidents by fine-tuning BERT Transformer, boosting productivity by 65%. Performed A/B Testing on the website to evaluate system effectiveness, led to a subsequent 10% increase in efficiency.
- Summarized long customer tickets using T5 Transformer and obtained a strong BERTScore of 0.95.
- Pioneered an incident-problem-change correlation modeling in TCS Hackathon using K-Means Clustering and converted the clustering model to an end-to-end product within 2 sprints.
Machine Learning Intern
September 2018 - January 2019
Tata Projects Limited, Raipur, INDIA
- Integral member of the Social Media Analytics team for the Government of Chhattisgarh, where I designed data models for analytical reporting. Created interactive Power BI dashboards and ad-hoc reports to support informed decision-making for relevant stakeholders
Portfolio Projects
Embark on a journey through my dedicated projects that showcase my quest for knowledge and practical application. Each project reflects my commitment to go beyond the usual, exploring new realms of possibility with a mix of curiosity and technical expertise. In the vast ocean of data, I sail with the compass of Machine Learning and Data Science, aiming to uncover insights that drive informed decisions and spark innovative solutions
- All
- Data Science
- Machine Learning (NLP)
- Software Engineering