Predictive Maintenance with Telematics Data

Developed a predictive analytics solution for a major automotive manufacturer to anticipate vehicle component failures using real-time telematics data. The system aimed to improve fleet reliability and reduce maintenance costs.

Key Contributions

• Built a data ingestion pipeline for streaming sensor data (e.g., engine temperature, brake pressure).
• Developed machine learning models for time-series failure prediction (87% accuracy).
• Created dashboards for operational teams to prioritize proactive service.

Industry: Automotive Manufacturing

Tech Stack: Python, Pandas, Scikit-learn, PySpark, AWS Lambda, Tableau

AI-Powered Biomarker Discovery

Led a research-focused initiative for a global life sciences organization to identify potential gene-drug interactions using advanced machine learning techniques. The objective was to accelerate the drug discovery pipeline by enhancing target identification and validation processes.

Key Contributions

• Cleaned and integrated high-dimensional genomics and proteomics datasets.
• Utilized NLP to extract biological relationships from unstructured scientific literature.
• Constructed and visualized molecular interaction networks to uncover key biomarkers.

Industry: Life Sciences / Bioengineering

Tech Stack: Python, Biopython, Scikit-learn, NetworkX, PubMed API, Jupyter

Customer Behavior Analytics

Created models to analyze customer behavior and transaction patterns, leading to targeted marketing strategies that increased customer retention by 20%.

Tools Used: SQL, Python, Tableau

Energy Management Optimization

Developed an analytics platform that optimizes energy consumption for commercial buildings, resulting in a 30% reduction in energy costs through actionable insights.

Tools Used: Microsoft Azure, R, Power BI

Fraud Detection System Enhancement

Improved the existing fraud detection system by implementing machine learning algorithms that identified suspicious transactions in real-time, reducing fraud-related losses by 40%.

Tools Used: Python, SQL, Apache Kafka, Qlik

Bioengineering Data Analytics

Analyzed bioengineering data to support research initiatives in pharmaceuticals. Developed data-driven insights that enhanced drug efficacy and patient outcomes.

Tools Used: Python, R, SQL, Tableau

Healthcare Analytics

Developed analytics dashboards to track patient health data, providing insights that informed better health interventions and improved patient outcomes.

Tools Used: SQL, R, Python, Qlik