Ayushi Lowanshi

Software Engineer

Mumbai, Maharashtra, India6 yrs 8 mos experience

Highly StableAI Enabled

Key Highlights

Developed AI solutions saving significant operational costs.
Expertise in machine learning and NLP with hands-on deployment.
Passionate about leveraging data for innovative solutions.

Stackforce AI infers this person is a Data Science and AI professional with a focus on EdTech and Transportation.

Contact

Skills

Core Skills

Artificial Intelligence (ai)Large Language Models (llm)Machine LearningData Analysis

Other Skills

Agentic AI DevelopmentExtract, Transform, Load (ETL)Python (Programming Language)Microsoft Power BIData CollectionExploratory Data AnalysisFeature EngineeringModel DevelopmentGenerative AITableauGen AISQLMicrosoft ExcelGoogle Sheetspower point presentation

About

AI professional with a Master's in Computer Science and Engineering. Currently, as a Technology Intern at upGrad Education Pvt. Ltd., I focus on developing and deploying AI-driven solutions that solve real-world problems and deliver significant business value. During my time at upGrad, I have developed several key projects: An LLM-powered chatbot that automated over 90% of learner queries, reducing support tickets by 70% and improving the overall learning experience. An AI-driven assignment autograder that saves the company 35L annually by reducing manual grading time by 80%. Automated pipelines, including a summarization engine, a transcription system with 92%+ accuracy, and a lead-extraction tool that increased qualified leads by 24%. My expertise is built on a strong foundation in machine learning, deep learning, and NLP, with hands-on experience in end-to-end project deployment. My skills include Python, SQL, C/C++, and frameworks like TensorFlow, PyTorch, and Flask. I am also proficient in AI and ML domains such as Generative AI, RAG, and Large Language Models (LLMs). I am passionate about leveraging data and AI to build innovative, efficient, and scalable solutions. I am eager to apply my skills to new challenges and contribute to impactful projects.

Experience

6 yrs 8 mos

Total Experience

3 yrs 2 mos

Average Tenure

3 mos

Current Experience

The innovation story

Software Engineer

Mar 2026 – Present · 3 mos · Mumbai, Maharashtra, India · Hybrid

Artificial Intelligence (AI)Agentic AI Development

Upgrad

Technology Intern

Jan 2025 – Sep 2025 · 8 mos · Hyderabad, Telangana, India · Hybrid

Automated resolution of 90%+ learner queries via an LLM-powered chatbot, improving student engagement scores and significantly reducing workload.
Developed an AI-driven assignment autograder that saved 35L annually by enhancing grading precision and reducing manual grading time by 80%.
Built and deployed three automated pipelines, including a summarization engine and a lead-extraction tool, boosting qualified leads by 24%.

Agentic AI DevelopmentLarge Language Models (LLM)

Uber

Mentorship

Jul 2024 – Sep 2024 · 2 mos · Indore, Madhya Pradesh, India · Remote

During my mentorship program, I focused on predicting Uber fare prices based on various influential factors. The goal was to develop an accurate model that estimates ride costs, assisting Uber in optimizing pricing strategies and enhancing customer satisfaction.
Project Overview:
Data Collection and Preparation:
I utilized a dataset containing historical Uber trip data, including pickup and dropoff coordinates, timestamps, distance traveled, and weather conditions. This involved cleaning the data by handling missing values and removing irrelevant columns to ensure integrity.
Exploratory Data Analysis (EDA):
I conducted univariate and bivariate analyses to uncover patterns and correlations. Visualizations highlighted trends in fare prices, emphasizing the effects of distance, time of day, and peak demand periods.
Feature Engineering:
I extracted key features from timestamps, such as the hour and day of the week, and developed new metrics like fare per mile for deeper insights into pricing dynamics.
Model Development and Evaluation:
I implemented multiple regression models, including Linear Regression, Random Forest, and XGBoost. Model performance was assessed using metrics like R² score, Adjusted R², and RMSE, with XGBoost demonstrating the highest accuracy.
Key Takeaways:
This project enhanced my understanding of machine learning applications and refined my data analysis skills. I learned the significance of feature engineering in model performance and appreciated how predictive analytics can drive business strategies in the ride-sharing industry.

Upgrad indore offline learning center

Data Science Trainee

Jan 2024 – Dec 2024 · 11 mos · India · On-site

Extract, Transform, Load (ETL)Machine learning

Indore municipal corporation

Sub Engineer

Mar 2019 – Dec 2024 · 5 yrs 9 mos · Indore, Madhya Pradesh, India · On-site

Performed large-scale data analysis on municipal datasets, unveiling key trends that informed decisions across multiple wards.
Developed interactive dashboards for real-time KPI tracking and automated reporting workflows, significantly speeding up processes by 99%.
Employed geospatial models to reduce complaint resolution time by 71% using advanced data visualization techniques.

Python (Programming Language)Microsoft Power BIData Analysis