Nikhil Rolawan

AI Researcher

Hyderabad, Telangana, India2 yrs 4 mos experience

AI EnabledHighly Stable

Key Highlights

Expert in building scalable generative AI applications.
Strong background in data-driven problem solving.
Passionate about continuous learning and innovation.

Stackforce AI infers this person is a Data Scientist specializing in Fintech and Healthcare with expertise in Machine Learning.

Contact

nilhil484@gmail.com LinkedIn

Skills

Core Skills

Machine LearningData Analysis

Other Skills

AWS SageMakerAbstract AlgebraAmazon Web Services (AWS)Applied Machine LearningArtificial Intelligence (AI)CC (Programming Language)C++CSS3Cloud ApplicationsCompetitive Marketing StrategiesComputer LiteracyComputer ScienceCustomer AnalysisCustomer Segmentation

About

Data Scientist with a strong math background, building scalable generative AI applications and intelligent agents. Experienced in multi language coding, data-driven problem solving, and design, with a passion for innovation and continuous learning. P.S : I like learning new technologies irrespective of my field of working.

Experience

2 yrs 4 mos

Total Experience

1 yr 4 mos

Average Tenure

11 mos

Current Experience

Virtusa

GenAI Consultant

Jul 2025 – Present · 11 mos · Hyderabad, Telangana, India · On-site

Iit roorkee

3 roles

LSTM Stock Price Forecasting for 20 Securities

Apr 2024 – Jul 2025 · 1 yr 3 mos

Constructed a pipeline for stock price prediction, leveraging 23 years of daily data for 20 stocks. The 3 stage pipeline is powered by an LSTM (Long Short-Term Memory) model, known for its ability to capture complex temporal patterns in sequential data. By training on extensive historical data, our model offers insights into future stock price movements, aiding investors in making informed decisions.

LSTMStock Price PredictionData PipelineMachine LearningData Analysis

Heart Diseases Risk Checker

Apr 2024 – Jul 2025 · 1 yr 3 mos

I have developed a heart disease risk assessment pipeline, deployed it using Docker and Streamlit for easy access. Our pipeline incorporates Preprocessing,training and Grid Search CV to fine-tune parameters and utilizes the Random Forest algorithm for accurate predictions. This tool enables efficient and reliable assessment of heart disease risk, contributing to proactive healthcare management.

Heart Disease Risk AssessmentDockerStreamlitRandom ForestGrid Search CVMachine Learning+1

Mall Segmentation K-Means Clustering

Feb 2024 – Jul 2025 · 1 yr 5 mos

Categorizing Mall Customers: Utilizing K-Means Clustering for Precise Segmentation. Our method analyzes Annual income and Spending score to identify distinct customer segments. This segmentation allows for tailored marketing strategies, optimized product offerings, and improved shopping experiences, driving increased foot traffic and revenue.

K-Means ClusteringCustomer SegmentationData AnalysisMachine Learning