TB

EXPERIENCE / TIME

Learning by building in real operational environments.

Experience across logistics, industrial systems, business optimization, and telecommunications in India and Bahrain.

RECORDED PERIODJANUARY 2024 — AUGUST 2026LATEST ROLE COMPLETED

TIME FIELD

Four periods, one moving practice.

JAN–FEB 20242024TELECOMMUNICATIONS
MAY–AUG 20242024ANALYTICS / BUSINESS OPTIMIZATION
DEC 2024–JAN 20252025INDUSTRIAL SYSTEMS
FEB–AUG 20262026COMPUTER VISION / LOGISTICS

ROLE / TRANSITION

The work changed as the systems became more real.

  1. January 2024 - February 2024

    Manama, Bahrain

    TELECOMMUNICATIONS FOUNDATION

    KEY EVIDENCE5+SYSTEMS REVIEWED

    Telecommunications Technology Intern

    Viacloud W.L.L.

    Telecommunications diagnostics, system performance review, and issue investigation.

    Purpose
    Telecommunications diagnostics and system-performance review.
    Contribution
    Reviewed logs, diagnostics, and module-level indicators across technical systems.
    Evidence
    5+ systems reviewed · 10+ technical issues contributed to

    What I learnedI learned to inspect technical systems through logs, diagnostics, and performance indicators.

    • Reviewed logs, diagnostics, and module-level performance indicators across multiple systems.
    • Contributed to bottleneck identification and technical issue resolution.
    • Worked with engineering teams across more than five systems or modules.

    StackLogs · Diagnostics · Performance indicators

  2. May 2024 - August 2024

    Al Hidd, Bahrain

    ANALYTICS / BUSINESS OPTIMIZATION

    KEY EVIDENCE50+NETWORK-RISK FINDINGS

    AI & Business Optimization Intern

    Foulath Holding

    Internal analytics, structured reporting, and risk-prioritization workflows.

    Purpose
    Internal analytics and business-optimization workflow support.
    Contribution
    Helped structure analytical reporting and surface risk findings for review.
    Evidence
    50+ network-risk findings surfaced for review

    What I learnedI connected analytical workflows with internal business decisions and investigation.

    • Developed an LLM-assisted internal analytics workflow using confidential business data.
    • Helped flag suspicious patterns for team investigation and structured reporting.
    • Built an ML-assisted workflow that surfaced more than 50 network-risk findings for review.

    StackAnalytics workflows · LLM-assisted analysis · Risk review

    Internal data, reports, workflows, and architecture are kept generalized.

  3. December 2024 - January 2025

    Hidd, Bahrain

    INDUSTRIAL SYSTEMS

    KEY EVIDENCE100K+TELEMETRY RECORDS

    Electrical & Instrumentation Intern

    Bahrain Steel

    Industrial telemetry, predictive maintenance, and stakeholder-facing technical analysis.

    Purpose
    Predictive-maintenance analysis using industrial motor telemetry.
    Contribution
    Engineered rolling-window features and compared model approaches for a normalized target.
    Evidence
    100k+ telemetry records · ~200 sensors · ~10 motor systems

    What I learnedI moved from analysis into predictive modeling with real industrial telemetry.

    • Built a predictive-maintenance workflow using more than 100,000 real telemetry records.
    • Worked with data from approximately 200 sensors across approximately 10 motor systems.
    • Engineered rolling-window features, compared Random Forest and XGBoost, and presented the project to internal stakeholders.

    StackPython · pandas · scikit-learn · XGBoost

  4. February 2026 — August 2026 · Completed

    Gurugram, India

    LATEST ROLE

    KEY EVIDENCE1,000IMAGE VALIDATION SET

    Computer Vision Intern

    Safexpress Pvt. Ltd.

    Applied AI, analytics, and automation work for real logistics workflows.

    Purpose
    Computer vision, analytics, and automation for logistics workflows.
    Contribution
    Contributed image-decoding, conversation-analysis, and ongoing SOP proof-of-concept work.
    Evidence
    1,000-image validation set · ~15,000 conversations analyzed · 18 confidential POC scenarios

    What I learnedI applied computer vision and analytics to practical logistics workflows.

    • Built a lightweight Code 128 waybill-decoding workflow for difficult, damaged, or low-quality images.
    • Analyzed approximately 15,000 historical BI Copilot conversations to identify intent patterns, failure points, and improvement opportunities.
    • Contributing to an ongoing computer-vision SOP compliance proof of concept for confidential logistics scenarios.

    StackPython · OpenCV · Snowflake · SQL · Computer vision

    Confidential logistics details are generalized, and the CCTV proof of concept is not described as a finished production deployment.

ACCUMULATED PRACTICE

Many systems, one clearer way of working.

TELECOMMUNICATIONSBUSINESS OPTIMIZATIONPREDICTIVE MAINTENANCECOMPUTER VISION
TECHNICAL WORK

Computer vision, predictive maintenance, telemetry, and analytics workflows.

OPERATIONS

Applied systems work grounded in logistics, industrial, and telecommunications contexts.

COMMUNICATION

Structured reporting, stakeholder presentations, and making technical findings usable.

DIRECTION / NEXT

Applied AI for real logistics workflows.

I applied computer vision and analytics to practical logistics workflows.

Confidential logistics details are generalized, and the CCTV proof of concept is not described as a finished production deployment.