Syed Ibrahim Afroz, Technical Analyst

Syed Ibrahim Afroz

Technical Analyst

C3i Solutions

Location
India - Hyderabad
Education
Master's degree, Data Science and Analytics
Experience
1 years, 7 Months

Share My Profile

Block User


Work Experience

Total years of experience :1 years, 7 Months

Technical Analyst at C3i Solutions
  • India
  • February 2020 to August 2021

- Provided technical support to clients
- Performed troubleshooting of Software issues and resolving them efficiently.
- Identified and classified incidents, such as technical failures, security breaches, and service interruptions, based on severity and impact.
- Maintained a comprehensive incident log, recording incident details, time of occurrence, affected systems, and initial assessment.
- Conducted initial triage and assessment of incidents, determining urgency and impact on business operations.
- Escalated incidents to appropriate teams or personnel, following established escalation procedures for timely response.
- Effectively communicated incident information to relevant stakeholders, including management and end-users, ensuring transparency and updates on resolution progress.
- Coordinated with technical teams to resolve incidents and monitored progress until satisfactory resolution.
- Conducted post-incident root cause analysis, identifying underlying issues and implementing preventive measures.
- Maintained detailed incident records, documenting resolution steps, and generating incident reports for management review.
- Ensured compliance with industry standards and regulatory requirements in incident management processes.

Education

Master's degree, Data Science and Analytics
  • at University Of Hertfordshire
  • January 2024

Projects: Credit card fraud detection using Machine Learning March 2023 - September 2023 - Created an efficient, accurate, and effective credit card fraud detection system by applying advanced machine learning methods. - Implemented and fine-tuned machine learning models, including Logistic Regression, - Decision Trees, Random Forest and XGBoost Classifier. - Evaluated model performance through rigorous testing and validation, iterating to achieve optimal results. - Utilized machine learning techniques to significantly improve the accuracy and efficiency of fraud detection.

Bachelor's degree, Computer Science Engineering
  • at Lords Institute of Engineering and Technology
  • September 2020

Specialties & Skills

Machine Learning
Service Desk
BMC Remedy

Languages

English
Expert
Hindi
Intermediate
Urdu
Intermediate

Training and Certifications

Advance Industry Certification in Java (Certificate)