Open to entry-level analyst roles · Hyderabad / remote

Sandeep Kumar Pulipati

Operational detail.
Analytical direction.

I’m Sandeep — a Business Operations and Seller Support professional translating 5+ years of structured investigation into practical data analysis with Excel, SQL and Python.

View projects ↓ Download resume ↓ Contact me ↗

05+years across operations
and support

90%SPS resolution
rate in resume

03completed analytics
projects

CurrentlySeller Support AssociateAmazon India · Hyderabad

signal / 01case → insight

toolkitExcel · SQL · Python

Scroll to explore

01Current baseHyderabad, India

02Primary experienceAmazon India · Seller Support

03Target rolesData / Operations / MIS Analyst

04Working styleAccurate · curious · structured

01 — The throughline

Good analysis starts with good questions.

My work has always sat close to the question behind the ticket: what happened, what evidence supports it, and what is the clearest next action?

At Amazon India, that means investigating seller issues, escalation histories, fulfillment problems and internal SOPs under quality and SLA requirements. In my analytics projects, the same habit becomes a workflow: structure the data, check its quality, find the pattern, and communicate what it means.

01Investigate before concluding

Trace the case history and supporting records before choosing a path.

02Make the logic visible

Document assumptions, formulas and decisions so the work can be reviewed.

03Keep the claim honest

Separate what I have demonstrated from what I am still learning.

02 — Work history

Experience with operational signal.

From high-volume seller support to AI data quality evaluation, each role built a different part of my analytical foundation.

May 2022 — Present

Amazon India · Hyderabad

Seller Support Associate

Current

Seller Support Associate with assignments across Selling Partner Support, T4 escalation investigations and a PSAS operations support project.

35/daySPS cases90%SPS resolution40+/dayT4 / PSAS tickets95%T4 / PSAS resolution

Selling Partner Support (SPS)

Handle approximately 35 seller cases per day with a 90% resolution rate, investigating reported issues and determining appropriate resolution steps.
Research internal knowledge resources, guidelines and SOPs; escalate cases when required.
Document investigations while following quality, productivity, policy and SLA requirements.

T4 + PSAS assignments

Handled 40+ tickets per day with a 95% resolution rate in complex seller escalations and fulfillment-center support.
Reviewed case histories, supporting information and internal policies to evaluate available evidence.
Determined resolution or escalation paths and coordinated with relevant internal teams.

Mar 2021 — May 2022

Teleperformance · Hyderabad

Analyst

14 months

Evaluated AI-generated responses for quality, accuracy and guideline compliance. Performed structured data tagging, validation and quality reviews with feedback across Language Reinforcement Learning (LRL) and Interactive Human-Agent Learning (IHAL) workflows.

Data validationQuality reviewStructured taggingGuideline compliance

Jun 2019 — Aug 2019

BharatPe · Hyderabad

Business Development Executive

3 months

Onboarded merchants onto the BharatPe digital payments platform and explained QR payment features, settlement workflows and platform benefits to prospective merchants.

03 — Capability map

What I use, what I’m building, what I know.

A candid skills map is more useful than a crowded keyword list.

AWorkplace-applied

Operations core

The strengths I use in real work: investigate carefully, follow the process, document the decision.

Case & escalation investigationRoot-cause triage across SPS and complex escalations

SOP research & SLA adherencePolicy interpretation, queue prioritization and compliance

AI data quality & taggingValidation, annotation and structured review

Operational documentationClear case notes, escalation summaries and Office workflows

BProject-demonstrated

Analytics toolkit

Microsoft ExcelBasic reporting + analysis

SQLFoundational querying

PythonFoundational EDA

Power BIIn progress

The bars indicate current evidence level, not a score or certification.

CIn practice

Next layer

Actively strengthening multi-table SQL joins, subqueries, Python data cleaning and Power Query / DAX patterns.

SELECT insight
FROM messy_data
WHERE question = clear;

04 — Selected evidence

Projects that turn tickets into patterns.

All completed projects use the same 250-row synthetic operations ticket dataset. Power BI is intentionally labeled as planned.

Excel operations and SLA performance dashboard

01 / Excel

CompletedOperations analysis

Excel Operations & SLA Performance

Helper formulas, summary tables and KPI views to isolate SLA bottlenecks across issue categories and support tiers.

Microsoft Excel250-row datasetDashboard

85.6%overall SLA18.8havg resolution96.8%QA pass rate

SQL business and operations case analysis output

02 / SQL

CompletedBusiness analysis

SQL Business & Operations Case Analysis

GROUP BY and CASE WHEN queries that compare ticket volume, turnaround time and SLA compliance by queue.

SQL / SQLite250-row datasetCase analysis

47fastest queue cases7.1havg order status55.6%Tier 1 volume

03 / Python

CompletedExploratory analysis

Python Exploratory Data Analysis

pandas-based inspection of missing values, first-contact resolution, category volume and tier SLA performance.

Python / pandas250-row datasetEDA chart

0missing values57.6%FCR rate250ticket rows

04 / Power BI

In progressDashboard architecture

Power BI Service Operations Dashboard

A planned interactive report for SLA compliance, backlog and QA pass rates by priority and merchant region.

Power BI / DAXScope onlyPBIX pending

Power Querydata typesDAXmeasuresPBIXnot yet final

Evidence pack

Open the working files.

Excel workbook ↓SQL queries ↓Python script ↓250-row CSV ↓

05 — Foundation

Education, languages & continuing practice.

Education

Bachelor of Science — Computers

Jagruti Degree and PG College
Osmania University · Hyderabad, Telangana

Graduated 2019

Languages

No separate certifications are listed in the available resume.

Source note

This portfolio uses the extracted resume PDF, genuine embedded images and project files available through the inspected public site. Unsupported claims are intentionally left out.

06 — Open channel

Let’s make the next
question useful.

I’m open to entry-level Data Analyst, Junior Data Analyst, Operations Analyst and MIS / Reporting Analyst opportunities in Hyderabad or remotely.

Send an email↗Call directly↗Open LinkedIn↗Inspect GitHub↗

Operational detail.Analytical direction.