Anmol Tripathi

Develop applied AI, machine learning, NLP, SQL, and Power BI solutions that support quality intelligence and operational decision-making. Build predictive analytics and text-classification workflows using Transformer and sparse-feature approaches, alongside RAG/LLM knowledge solutions and reusable Python data pipelines. Partner with quality and operations stakeholders to turn complex business data into reliable, measurable insights and automation opportunities.

Built a wearable-ring temperature research workflow for approximately 135 participants. Performed SQL extraction, data normalization, temporal feature engineering, sequence generation, and validation. Evaluated SVM, LSTM/BiLSTM, CNN, Autoencoder, ARIMA, and SARIMA models to investigate longitudinal and circadian patterns and communicate research findings.

Analyzed approximately 80,000–100,000 monthly sales records across more than 30 product categories. Built Tableau dashboards to support demand and inventory decisions, contributed to stock-level improvements, and trained 8–10 team members.

Analyzed more than 10,000 daily network metrics, investigated anomalies and incidents, and automated data extraction, validation, and reporting using Python, SQL, and Excel. Developed a network-failure prediction proof of concept and enhanced Tableau KPI dashboards for operational visibility.

Monitored enterprise network infrastructure and investigated service incidents, alerts, and performance anomalies. Analyzed large-scale network metrics and supported data extraction, validation, and reporting using Python, SQL, Excel, and Tableau. Contributed to operational KPI dashboards and continuous improvements in network reliability and service visibility.

Completed technical training in network operations and supported monitoring, incident analysis, reporting, and service-quality activities within a global telecommunications environment.

GPA: 3.889 / 4.0. Graduate coursework focused on Machine Learning, Natural Language Processing, Data Mining, Data Analysis and Visualization, Statistical Programming, Big Data Analytics, Cloud Computing, Advanced Database Concepts, and Applied NLP.

Focused on data science, business analytics, machine learning, statistical analysis, data visualization, and applying analytical insights to business decision-making.

Built a strong foundation in electronics, telecommunications, programming, signal processing, engineering mathematics, and technical problem-solving—providing the engineering base for later work in data science and applied AI.