Data Analyst with extensive experience in IT and telecommunications, specializing in SQL, Python, and Power BI for data extraction, validation, visualization, and reporting. Proven ability to transform complex datasets i…
Data Analyst with extensive experience in IT and telecommunications, specializing in SQL, Python, and Power BI for data extraction, validation, visualization, and reporting. Proven ability to transform complex datasets into actionable insights that support business decision-making and operational efficiency. Experienced in IT Service Management (ITSM), project coordination, and cross-functional collaboration within fast-paced environments. Strong understanding of data quality, risk assessment, and performance monitoring, with a focus on delivering accurate and reliable data-driven solutions. Adept at identifying trends, optimizing processes, and supporting strategic initiatives through analytical thinking and problem-solving skills.
Designed and containerized machine learning workloads using Docker, building reusable Docker microservices (MS) to support scalable ML inference and training pipelines.
Deployed containerized ML services on Google Cloud Platform, including Google Cloud Run, enabling serverless execution and simplified operational management.
Improved and maintained CI/CD pipelines using GitHub Actions, supporting both manual dispatch workflows and automated triggers (push, pull request, scheduled, and environment-based triggers).
Integrated CI/CD pipelines to automate build, test, container image creation, and deployment, improving reliability and reducing manual intervention.
Implemented resource monitoring and performance tracking for long-running ML inference and training jobs, aligning with OSS-style FCAPS principles (fault, performance, capacity).
Worked on WhisperX and NVIDIA NeMo pipelines, including Voice Activity Detection (VAD) and speaker diarization model training, evaluation, and optimization.
Developed Python-based data analytics and monitoring utilities to analyze processing time, resource utilization, and model performance.
Collaborated in Agile, sprint-based, pod-oriented teams, actively participating in sprint planning, daily stand-ups, backlog grooming, reviews, and retrospectives.
Partnered closely with DevOps, ML, and platform teams to deliver production-grade, cloud-native ML services aligned with enterprise OSS automation standards.
Designed and containerized machine learning workloads using Docker, building reusable Docker microservices (MS) to support scalable ML inference and training pipelines.Deployed containerized ML services on Google Cloud Platform, including Google Cloud Run, enabling serverless execution and simplified operational management.Improved and maintained CI/CD pipelines using GitHub Actions, supporting both manual dispatch workflows and automated triggers (push, pull request, scheduled, and environment-based triggers).Integrated CI/CD pipelines to automate build, test, container image creation, and deployment, improving reliability and reducing manual intervention.Implemented resource monitoring and performance tracking for long-running ML inference and training jobs, aligning with OSS-style FCAPS principles (fault, performance, capacity).Worked on WhisperX and NVIDIA NeMo pipelines, including Voice Activity Detection (VAD) and speaker diarization model training, evaluation, and optimization.Developed Python-based data analytics and monitoring utilities to analyze processing time, resource utilization, and model performance.Collaborated in Agile, sprint-based, pod-oriented teams, actively participating in sprint planning, daily stand-ups, backlog grooming, reviews, and retrospectives.Partnered closely with DevOps, ML, and platform teams to deliver production-grade, cloud-native ML services aligned with enterprise OSS automation standards.
Processed tax-related documents and cheques, performed accurate data entry, and maintained confidential financial records in compliance with CRA policies.
Utilized government IT systems ensuring data security and integrity while handling sensitive information.
Processed tax-related documents and cheques, Utilized government IT systems ensuring data security and integrity
Directed ERP (Odoo) and e-commerce projects, integrating SQL and Power BI dashboards to improve financial and operational reporting.
Worked on data validation and transformation workflows (ETL) for HR, finance, and compliance modules.
Partnered with stakeholders to ensure data-driven decision-making aligned with business and regulatory standards.
Produced user documentation, trained end-users, and supported post-implementation analytics reporting.
Directed ERP (Odoo) and e-commerce projects, integrating SQL and Power BI dashboards to improve financial and operational reporting.Worked on data validation and transformation workflows (ETL) for HR, finance, and compliance modules.Partnered with stakeholders to ensure data-driven decision-making aligned with business and regulatory standards.Produced user documentation, trained end-users, and supported post-implementation analytics reporting.
Designed and implemented IoT solutions, building data pipelines for device telemetry collection, cleaning, and transformation for analytics dashboards.
Multiple programming language applied for data wrangling, anomaly detection, and system integration.
Collaborated with business teams to translate IoT data into device monitoring and performance insights.
Delivered documentation and compliance reporting to support data-driven IoT operations.
Designed and implemented IoT solutions, building data pipelines for device telemetry collection, cleaning, and transformation for analytics dashboards.Multiple programming language applied for data wrangling, anomaly detection, and system integration.Collaborated with business teams to translate IoT data into device monitoring and performance insights.Delivered documentation and compliance reporting to support data-driven IoT operations.
Led financial and compliance data projects ensuring SOC 1, SOC 2, and PCI DSS readiness.
Built dashboards and SQL-driven reports to monitor risks, KPIs, and remediation progress.
Partnered with risk and audit teams to perform data analysis on regulatory findings, improving risk frameworks and reporting accuracy.
Applied Jira/Confluence to document and manage risk-related data workflows.
Led financial and compliance data projects ensuring SOC 1, SOC 2, and PCI DSS readiness.Built dashboards and SQL-driven reports to monitor risks, KPIs, and remediation progress.Partnered with risk and audit teams to perform data analysis on regulatory findings, improving risk frameworks and reporting accuracy.Applied Jira/Confluence to document and manage risk-related data workflows.
Led network infrastructure projects ensuring SLA adherence and regulatory compliance.
Created Visio diagrams and MS Project schedules to manage deliverables and resources.
Maintained stakeholder communication and issue tracking using in-house ITSM tools.
Led network infrastructure projects ensuring SLA adherence and regulatory compliance, Maintained stakeholder communication and issue tracking using in-house ITSM tools
Supported ERP/telecom software projects, handling system analysis, configuration, and testing.
Produced deployment documentation and troubleshooting guides for operational continuity.
Supported ERP/telecom software projects, handling system analysis, configuration, and testing.Produced deployment documentation and troubleshooting guides for operational continuity.
Directed OSS/NOC operations, creating automated ELT pipelines for network KPI data extraction, transformation, and reporting.
Developed Web-based and Excel-based dashboards to track SLA adherence, incident trends, and risk indicators.
Authored technical documentation and data-driven troubleshooting procedures to support operational resilience.
Directed OSS/NOC operations, creating automated ELT pipelines for network KPI data extraction, transformation, and reporting.Developed Web-based and Excel-based dashboards to track SLA adherence, incident trends, and risk indicators.Authored technical documentation and data-driven troubleshooting procedures to support operational resilience.
Worked on large-scale IT/telecom infrastructure projects across planning, execution, and closure.
Coordinated vendors and stakeholders, ensuring alignment with compliance and ITSM processes.
Delivered large-scale telecom data analytics tasks, including fraud risk assessment and compliance reporting.
Designed and implemented OSS-based data reporting tools (SQL, SNMP, APIs) for service assurance and fraud detection.
Collaborated with risk teams to perform data analysis on fraud patterns and network anomalies, strengthening compliance frameworks.
Delivered audit-ready reports to leadership using visualization and data mapping techniques.
Worked on large-scale IT/telecom infrastructure projects across planning, execution, and closure.Coordinated vendors and stakeholders, ensuring alignment with compliance and ITSM processes.Delivered large-scale telecom data analytics tasks, including fraud risk assessment and compliance reporting.Designed and implemented OSS-based data reporting tools (SQL, SNMP, APIs) for service assurance and fraud detection.Collaborated with risk teams to perform data analysis on fraud patterns and network anomalies, strengthening compliance frameworks.Delivered audit-ready reports to leadership using visualization and data mapping techniques.
Installed, configured, and maintained gateways, routers, voice switches.
Created technical documentation for installation and maintenance and provided client training.
Developed a Machine Learning-based Intrusion Detection System (IDS) using Python to identify network anomalies and potential cyberattacks. Implemented and compared multiple classification models, including Decision Tree and other built-in algorithms, to evaluate detection performance. The project focused on both anomaly detection and attack classification using benchmark datasets. Model performance was assessed based on accuracy, precision, and false positive rates. The study highlights the effectiveness of ML techniques in improving detection of malicious network activity.
Implemented a Low-light Image Enhancement technique using MATLAB to improve image brightness and visibility in poorly lit conditions. Applied Gaussian filtering and image processing methods to enhance contrast and overall image clarity. The project focused on improving visual quality while preserving important details. Performance was evaluated on dark images to assess enhancement effectiveness. Additional work addressed limitations such as overexposure, aiming to reduce excessive brightness in highlighted regions.
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