Summary
Overview
Work History
Education
Skills
Timeline
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Sushil Ram Achamwad

Seattle

Summary

Analytics professional with 9+ years of experience in analytics, data science, and project management

Overview

10
10
years of professional experience

Work History

Senior BIE

Amazon
01.2024 - Current
  • Architected and launched a secure, serverless data science workbench with AWS stack, transforming weekly reporting into an automated, diagnostic engine and saving 80% of manual analysis time.
  • Enabled self-service workflows for time series forecasting, attribution analysis, and explainable predictive modeling using a Python and Streamlit-based web application.
  • Integrated LLM-powered summaries to automatically identify and explain key business drivers, shifting analyst focus from data gathering to strategic action.
  • Established the single source of truth for Customer Experience analytics, saving over 300 BIE hours monthly by launching a centralized, self-service QuickSight dataset.
  • Engineered a 'One Big Table' data model by unifying 1.6 billion records (>1TB), providing a holistic view of the customer journey.
  • Embedded complex, level-aware calculations into the data model to empower non-technical users with robust self-service deep-dive capabilities, reducing dependency on analyst teams.
  • Automated root cause analysis for repeat customer contacts by architecting an LLM-powered diagnostic platform, directly supporting a VP-level initiative to reduce repeat contact rates.
  • Built a scalable, serverless AWS solution capable of processing over 2,000 customer transcripts per hour, completely eliminating the need for manual review.
  • Deployed a modular DSPy pipeline utilizing advanced prompting techniques (e.g., Chain-of-Thought, Few-Shot, LLM-as-a-Judge) to accurately identify and surface actionable defect patterns.
  • Resolved a critical, longstanding visibility gap into customer service drivers by developing an LLM-based classification model with >90% accuracy, now covering 85% of all global contacts.
  • Automated the mapping of 5,600+ granular issue codes into 15 actionable contact reason groups, creating a standardized taxonomy for trend analysis.
  • Combined topic modeling with sophisticated classification prompts to deliver a solution that provides unprecedented clarity on why customers contact support.
  • Delivered $7M in annual concession savings by launching an analytics dashboard to identify, quantify, and mitigate customer returns abuse in the Canadian marketplace.
  • Provided actionable intelligence on key defect drivers, including 'Delivered Not Received' abuse patterns and compliance with OTP-enabled secure deliveries.
  • Empowered leadership with a QuickSight-based tool to monitor the financial impact of mitigation strategies and track defect reduction in real-time.

Data Scientist

OYO Hotels
08.2019 - 12.2023
  • Enhanced revenue performance by developing and implementing several dynamic pricing modules in Python.
  • Deployed a reinforcement learning model (KASPER) that yielded a +13% revenue uplift across a 30-property trial.
  • Created a Multi-Armed Bandit framework to systematically experiment with and identify the most effective pricing drivers.
  • Built predictive machine learning models to improve customer experience and forecast booking behavior.
  • Implemented a Random Forest hotel recommendation algorithm for the consumer app and website using historical booking data.
  • Developed a predictive model to accurately forecast booking cancellations by analyzing user and hotel history.
  • Engineered automated systems for performance monitoring and fraud detection to improve financial accuracy.
  • Created an issue tracker using the Prophet library to automatically flag significant anomalies in key metrics like RevPAR and Occupancy.
  • Developed a fraud detection system to identify and curb suppressed walk-in revenue at the hotel level.
  • Drove data-driven decision-making by creating a comprehensive suite of business intelligence dashboards.
  • Built dashboards in Metabase and Tableau providing end-to-end visibility of the customer funnel, from impressions to revenue.
  • Migrated all critical reporting from static Excel sheets to track channel performance and hotel-level contribution margins in real-time.

Deputy Manager - MIS

Shapoorji Pallonji Constructions
Pune
07.2015 - 05.2018
  • Crafted optimized operation strategies and built Master Construction Plans (MCPs) using Oracle Primavera and Microsoft Project for 30+ construction projects creating an impact of ∼$5m in revenue.
  • Reduced construction material quantity estimation error by 3% by introducing use of 3D models for project designs.

Education

Master of Science - Business Analytics and Information Management

Purdue University
West Lafayette, IN
05-2019

Bachelor of Technology (Hons) - Civil Engineering

Indian Institute of Technology (IIT), Bombay
Mumbai, India
05.2015

Skills

  • Python programming
  • Business intelligence
  • Project management
  • SQL programming
  • Data visualization
  • Machine learning
  • Data modeling
  • Predictive analytics
  • Statistical analysis
  • Strategic thinking

Timeline

Senior BIE

Amazon
01.2024 - Current

Data Scientist

OYO Hotels
08.2019 - 12.2023

Deputy Manager - MIS

Shapoorji Pallonji Constructions
07.2015 - 05.2018

Master of Science - Business Analytics and Information Management

Purdue University

Bachelor of Technology (Hons) - Civil Engineering

Indian Institute of Technology (IIT), Bombay

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