SK
Open to Junior Data Analyst roles

Turning raw
operational data
into clear decisions.

I'm Shubham — a data analyst based in Kalaburagi, India, working across SQL, Python, Power BI and Advanced Excel to catch the pattern hiding in the caseload.

0%
QUALITY SCORE
0%
FEWER REPEAT DEFECTS
0+
RECORDS AUDITED / WK
0m
SAVED WEEKLY BY MACROS
// PRIMARY STACK
SQL / MySQL
Power BI
Advanced Excel
Python
LLM-Assisted Research
SCROLL

Detail is the whole job.

I spend my days inside shipment records, system logs, and catalog data — reconciling what should match, flagging what doesn't, and tracing root causes before they become recurring defects.

Currently a Catalog Specialist at Amazon, I review a daily caseload of ~50 records and have built Excel macros that cut manual reporting time and sharpened turnaround. Before that, as a Support Ops Specialist, I ran deep-dive investigations across shipment, tracking, and system-log data.

I also lean on LLM tools like Claude and ChatGPT with structured prompting to speed up research, synthesis, and reporting — treating them as part of a modern analyst's toolkit, not a shortcut around the analysis itself.

99.6%
PEAK QUALITY SCORE
100%
SLA COMPLIANCE
1
EXCEL MACRO BUILT
8.00
CGPA, B.E. ECE

A toolkit built for finding the signal.

Grouped the way I actually use them — from querying and cleaning, to reporting, to the investigative thinking behind it.

DB

Data & Querying

  • SQL / MySQL
  • Data Cleaning & Validation
  • Quantitative & Trend Analysis
BI

Reporting & BI

  • Power BI Dashboards
  • Advanced Excel (Pivots, XLOOKUP)
  • Excel Macro Automation
RC

Investigation

  • Root-Cause Analysis
  • Pattern & Anomaly Detection
  • Process Documentation (SOPs)
PY

Applied Technical

  • Python
  • LLM-Assisted Research & Prompting
  • Stakeholder Communication

Two years, two seats at Amazon.

Catalog Specialist Dec 2025 – Present
Amazon
  • Analyze a daily caseload of ~50 shipment, system-log, and catalog records (110+ weekly) to identify discrepancies, patterns, and root causes, ensuring policy-compliant, accurate resolutions.
  • Built 3 Excel macros to automate recurring data-validation and reporting tasks, saving ~40 minutes per week and improving analysis turnaround.
  • Deliver data-driven recommendations to cross-functional teams that improved catalog accuracy and operational efficiency while reducing recurring defects.
  • Maintain rigorous data quality and documentation standards, sustaining a ~99% quality score and full SLA compliance.
Support Ops Specialist Dec 2024 – Dec 2025
Amazon
  • Conducted deep-dive, evidence-based investigations on inventory discrepancies by reconciling shipment data, tracking reports, and system logs across multiple internal tools.
  • Identified recurring operational issues through pattern analysis, reducing repeat defects by ~15% and improving investigation efficiency.
  • Maintained 100% SLA compliance and a 99.6% quality score while documenting findings and SOPs for audit readiness.
  • Partnered with Operations, Finance, and Risk teams to translate raw data into actionable insights informing reimbursement and process decisions.

Where data meets diagnosis.

Anatomical lung illustration used as the base for CNN-based respiratory disease detection
CNN Model · anomaly markers & scan sweep overlaid on real anatomy

Radiological Image Analysis Using Raspberry Pi

Built a CNN-based diagnostic model using Python, TensorFlow, and OpenCV to detect respiratory diseases from chest X-rays — applying quantitative modeling and data analysis techniques to improve diagnostic speed and accuracy, deployed on a Raspberry Pi.

Python TensorFlow OpenCV CNN Raspberry Pi

Foundations.

Bachelor of Engineering — Electronics & Communication Engineering

BMS Institute of Technology & Management, Bengaluru
Dec 2020 – May 2024
🎓 CGPA: 8.00

Recognition

🏆
"Excellence" Award
MFI FBA Operations, Amazon

Languages

EnglishHindiKannada

Let's talk about your data.

Open to Junior Data Analyst roles in market research and technology intelligence. Based in Kalaburagi, Karnataka — happy to work remote or relocate.