Hello, I'm

Akshata Salunkhe

Get To Know More

About Me

Experience

4+ years
Data Scientist and Analyst

Education

BTech in Electronics and Telecommunication
MS in Artificial Intelligence and Business Analytics

A pioneer turned into a coding enthusiast. My projects and research focus on how Machine Learning systems interact with our societies and the downstream effects of introducing AI to our society. I work on creating data pipelines to extract, load and transform to Datawarehouse and handled data security, and privacy. And yes, in these thrilling days of the LLM boom, I've found a new playground where words and algorithms dance together, unveiling insights and challenges alike. I have worked under multiple organizations from Tech port solutions to Eaton in diverse roles and tech stacks comprising of Coding languages, automation or AI / ML projects.

Explore My

Skills

Languages

SQL

Experienced

Python

Experienced

R

Experienced

C++

Experienced

JavaScript

Experienced

Tools, Technologies and Database

PostgreSQL

Experienced

Machine Learning

Experienced

AWS

Experienced

Git

Experienced

Tableau

Experienced

PowerBI

Experienced

Power Apps (Power Automate)

Intermediate

4+ YEARS OF EXPERIENCE

My Resume

Job Experience

Data Analyst

DHL Express, Plantation (Jan 2025 - Present)

Built a Retrieval-Augmented Generation (RAG) chatbot using LangChain and vector databases to streamline customs clearance, enabling semantic search over regulatory documents and tariff codes which reduced clearance time by 60% and minimized compliance errors.
Designed and executed A/B tests across global gateway clusters to optimize pre-clearance messaging, achieving a 9% lift in label-checkout completion and contributing to $2M in projected revenue.
Engineered high-performance Snowflake data marts by building a scalable Star Schema data model and implementing clustering and materialized views, reducing query latency by 24% while ensuring data integrity through automated SQL validation frameworks.
Developed scalable Power BI dashboards with incremental refresh policies and dynamic DAX measures to track critical risk KPIs (COA, Bonded, Unmanifested), slashing manual reporting time by 60% and enabling real-time operational visibility.
Automated compliance checks using a Python script triggered by Power Automate to query Snowflake for data gaps, reducing reporting time by 80% (Weekly to Daily) and enabling teams to clear stalled inventory faster.

Data Scientist Researcher

Coke Florida : University of South Florida, Tampa (2023 - 2024)

Python | Machine Learning | Tableau | Excel

Developed a Random Forest classification model to support the "World Without Waste" initiative, achieving 85% accuracy in identifying high-potential recycling zones and guiding the expansion of the Reverse Vending Machine (RVM) network.
Engineered Python-based feature pipelines to integrate historical collection logs, sales density, and demographic data, enabling exploratory analysis that uncovered key drivers of consumer recycling behavior.
Designed a demand-based logistics strategy to transition collection schedules from fixed intervals to volume-based triggers, reducing fleet transportation frequency by 15% and lowering carbon emissions by 12%.

Proctor

SAS, University of South Florida, Tampa (Aug 2023 - Nov 2023)

Attention to Detail: Ensured the accurate verification of student identities and adherence to examination protocols, maintaining a secure and fair testing environment.
Communication: Effectively conveyed exam rules and procedures, addressed student questions, and reported incidents to maintain examination integrity.
Time Management: Successfully managed exam schedules and materials distribution, ensuring exams commenced and concluded on time while handling multiple tasks efficiently.

Associate Data Engineer

Eaton India Innovation Center, India (2021 - 2023)

Designed high throughput distributed systems using Spark SQL and Python to integrate 10M+ records from heterogeneous sources into a unified AWS data lake, optimizing execution plans to handle complex financial transformations efficiently.
Deployed dbt models within a CI/CD ecosystem (AWS CodePipeline) to build incremental, tested data marts, automating the promotion of code from development to production to ensure data lineage and reproducibility.
Automated third-party data ingestion via Python (REST APIs) and AWS Glue, implementing robust error handling and CloudTrail monitoring to ensure zero data loss during critical reporting windows.
Developed automated data pipelines using Python for custom ETL and SQL for dimensional modeling (Star Schema) to feed Power BI dashboards, eliminating 15+ hours of manual weekly aggregation and improving global financial reporting accuracy.
Built interactive pricing analytics dashboards to monitor quote win-rates and discount elasticity, empowering sales teams to identify real-time margin leakage and driving a +2.1pp gross margin expansion.
Applied Six Sigma principles to streamline the end-to-end data delivery lifecycle, identifying critical workflow bottlenecks through root cause analysis to drive a 30% reduction in cycle time and operational overhead.

Education

Master of Science in Artificial Intelligence and Business Analytics

University of South Florida, Tampa (2023 - 2024)

Data Mining, Machine Learning, Advanced Database Management System, Advanced System Analysis and Design, Data Warehouse, Data Science Programming, Big Data

Bachelor of Technology (BTech) in Electronics And Telecommunication

MKSSS's Cummins College of Engineering Pune, India (2017 - 2021)

Web Development, Object Oriented Programming Language, Database Management System, Data Structures and Algorithms, Machine Learning

Visit My Portfolio and Keep Your Feedback

My Projects

Total repositories

Weather Data Analysis - AWS Cloud Pipeline

The weather data analysis project uses AWS cloud pipeline to process and analyze weather data, providing insights and visualizations for better decision-making. visit

HeartWellness

The Heart Wellness project uses machine learning to predict heart disease and stroke risks, providing personalized health insights and consultations through a secure, user-friendly website.visit

PII Redaction

The PII Redaction from vCons project enhances data privacy by using NLP to identify and redact PII from conversations, ensuring regulatory compliance and client trust visit

State of Tampa

This project uses advanced data analysis and machine learning to compare Tampa Bay's affordability and talent availability with other MSAs, providing insights for regional development and economic planning.visit

Insightscribe-Blog-Generation

The Blog Generation project automates high-quality blog creation using OpenAI's language models, offering a user-friendly application for efficient content generation based on user prompts.visit

Stock Marketing Prediction

The Stock Market Price Prediction project uses machine learning and PySpark to analyze historical data and predict stock prices, providing investors with real-time insights and trends for informed decision-making.visit

Contact With Me