Anmol Tripathi

1) Designed and deployed an internal AI-powered quality intelligence agent using RAG and LLMs, making source-grounded product-quality knowledge accessible to approximately 50 potential users across R&D and quality teams.

2) Integrated the agent with GCS records dating back to 2015 and thousands of NCN PDFs, implementing ingestion, chunking, embeddings, semantic retrieval, contextual prompting, an

1) Led the development of deep-learning and predictive-analytics workflows using longitudinal wearable-ring temperature data from approximately 135 research participants to estimate labor timing and investigate maternal temperature patterns.

2) Extracted per-second observations and minute-level aggregations from SQL Server, then performed data cleaning, statistical analysis, normalization, tempor

1) Promoted from Student Assistant to Student Assistant Manager within four months, combining retail operations, team leadership, and applied analysis of sales, inventory, customer, and marketing data.

2) Analyzed approximately 80,000–100,000 monthly sales records across 30+ product categories using Excel, identifying demand patterns, inventory movement, replenishment requirements, and stock risk

1) Analyzed customer, sales, and purchase-pattern data using Excel to identify trends supporting marketing, promotional, and store-level decisions.

2) Cleaned and validated recurring retail datasets using formulas, filters, lookup functions, and structured worksheets, maintaining accurate sales and customer reporting.

3) Prepared weekly visual reports covering sales performance, customer behavio

1) Analyzed network-performance, incident, and equipment data using Python and SQL to identify anomalies, recurring fault patterns, service risks, and opportunities for proactive intervention across Cisco and Juniper environments.

2) Developed and evaluated a predictive machine-learning proof of concept for network-failure detection, achieving approximately 85% accuracy during internal model eval

1) Monitored enterprise network infrastructure and analyzed more than 10,000 network-performance metrics daily, identifying anomalies, service degradation, recurring faults, and emerging reliability risks across Cisco and Juniper environments.

2) Used Python, SQL, and Excel to extract, clean, validate, and analyze network-performance, incident, and equipment data for proactive monitoring, fault i

1) Completed structured training in enterprise network operations, incident management, monitoring, and troubleshooting across Cisco and Juniper routing and switching environments.

2) Monitored network alarms, performance indicators, device logs, and service events, assisting with issue identification, documentation, escalation, and resolution.

3) Developed foundational capabilities in Python, S

Grade: 3.889/4.000

Activities and societies: Awarded an approximately 33% merit-based tuition scholarship during both the second and third semesters. Applied Python, SQL, predictive modeling, and analytical methods to structured, unstructured, and longitudinal datasets. Contributed to healthcare research at the College of Nursing by developing and comparing LSTM, Bidirectional LSTM, CNN, and Autoencoder models for maternal temperature data and labor-timing estimation.

Completed a Master of Science in Data Science with a 3.889/4.000 GPA, developing advanced capabilities in machine learning, statistical analysis, data engineering, visualization, and responsible data-driven decision-making.

Completed a Master of Science in Data Science with a 3.889/4.000 GPA, developing advanced capabilities in machine learning, statistical analysis, data engineering, visualization, and responsible data-driven decision-making.

• Awarded an approximately 33% merit-based tuition scholarship during both the second and third semesters in recognition of strong academic performance.

• Applied Python, SQL

Grade: 4.00/4.00

Activities and societies: Awarded a 40% merit-based tuition scholarship. Completed and consolidated 13 end-to-end projects spanning statistics, regression, classification, clustering, PCA, NLP, time-series forecasting, customer segmentation, retail analytics, and biomedical machine learning. Applied Python, pandas, NumPy, SciPy, scikit-learn, and Jupyter across data preparation, feature engineering, model development, validation, evaluation, and business interpretation.

Completed an applied Post Graduate Program in Data Science and Business Analytics with a 4.00/4.00 grade.

Completed an applied Post Graduate Program in Data Science and Business Analytics with a 4.00/4.00 grade.

• Awarded a 40% merit-based tuition scholarship based on strong performance in the program’s admission assessment.

• Completed and consolidated 13 end-to-end projects spanning statistics, regression, classification, clustering, PCA, NLP, time-series forecasting, customer segmentation, retail

Completed undergraduate studies in Electronics and Telecommunications Engineering with an 8.99/10.00 grade.

• Awarded and maintained a 50% merit-based tuition scholarship across all eight semesters in recognition of sustained academic performance.

• Built foundations in communication systems, electronics, computer networks, signal processing, engineering mathematics, probability, statistics, lin

Completed Senior Secondary Education (Class XII) in the Science stream with an overall score of 91.6%.

Subject scores:
• Mathematics: 95%
• English: 95%
• Chemistry: 90%
• Physics: 82%
• Physical Education: 97%

Developed a strong foundation in mathematics, scientific reasoning, quantitative problem-solving, and analytical thinking.

Completed Secondary School Education (Class X) with an overall score of 84%, developing foundational knowledge across mathematics, science, English, and social studies.