07/28/2026 updated
100 % available
Data Analytics & AI Engineer | Big Data, SQL, Python, BI & Visualization
Bengaluru, India
Only remote
Graduate in M.Sc. in Big Data Analytics About me
? I'm Manjusha Making data spill secrets and AI do the heavy lifting. A data and AI enthusiast with a passion for building intelligent solutions and solving real-world problems. I spend my days exploring data, uncovering patterns, and occasionally convincing AI models to cooperate.
A/B TestingData AnalysisBusiness IntelligenceBig DataData VisualizationMachine LearningMicrosoft Business IntelligencePredictive AnalyticsSQL DatabasesVisual AnalyticspandasData Analytics
Data Analysis & Query Tools
Proficiency in SQL, Python (Pandas, NumPy), R, Excel (Pivot Tables, VLOOKUP, Dashboards), and Google Workspace (Sheets, Docs) for querying, processing, and analyzing complex datasets.
BI & Visualization
Expertise in Power BI, Tableau, and Matplotlib for KPI tracking, dashboard development, and data storytelling, translating complex data into actionable business insights.
Statistical Analysis & Predictive Analytics
Strong foundation in hypothesis testing, A/B testing, regression analysis, ANOVA, time series forecasting, and predictive analytics to support data-driven decision-making.
Data Quality & Anomaly Detection
Experience in data cleaning, data wrangling, ETL workflows, and fraud and anomaly detection modeling to ensure data integrity and reliability.
Machine Learning
Development and validation of machine learning models including Random Forest, Logistic Regression, ResNet50, SVM, and CNN-based approaches for classification and anomaly detection tasks.
Cloud & Deployment
Hands-on experience deploying applications using Flask and AWS EC2, including cloud-deployed appointment booking systems.
Forecasting & Scenario Modeling
Building forecasting models to predict trends and evaluate outcomes under different policy scenarios, with results distilled into actionable infrastructure recommendations.
Dashboard & Reporting Solutions
Building interactive dashboards and reporting solutions for operational monitoring and fraud/anomaly detection, delivering insights to cross-functional teams.
Proficiency in SQL, Python (Pandas, NumPy), R, Excel (Pivot Tables, VLOOKUP, Dashboards), and Google Workspace (Sheets, Docs) for querying, processing, and analyzing complex datasets.
BI & Visualization
Expertise in Power BI, Tableau, and Matplotlib for KPI tracking, dashboard development, and data storytelling, translating complex data into actionable business insights.
Statistical Analysis & Predictive Analytics
Strong foundation in hypothesis testing, A/B testing, regression analysis, ANOVA, time series forecasting, and predictive analytics to support data-driven decision-making.
Data Quality & Anomaly Detection
Experience in data cleaning, data wrangling, ETL workflows, and fraud and anomaly detection modeling to ensure data integrity and reliability.
Machine Learning
Development and validation of machine learning models including Random Forest, Logistic Regression, ResNet50, SVM, and CNN-based approaches for classification and anomaly detection tasks.
Cloud & Deployment
Hands-on experience deploying applications using Flask and AWS EC2, including cloud-deployed appointment booking systems.
Forecasting & Scenario Modeling
Building forecasting models to predict trends and evaluate outcomes under different policy scenarios, with results distilled into actionable infrastructure recommendations.
Dashboard & Reporting Solutions
Building interactive dashboards and reporting solutions for operational monitoring and fraud/anomaly detection, delivering insights to cross-functional teams.
Experience
Professional experience0 - 5 years
Freelancer since2026
Languages
EnglishFluentHindiBasic knowledge
Project history
Designed and executed statistical A/B tests using two-proportion z-tests to evaluate landing page performance and quantify business impact. Cleaned and analyzed user behavior data, presenting findings through visualizations and reports using Python, Pandas, Statsmodels, Matplotlib, and Excel.
Developed a Parkinson's disease detection model achieving 97.47% accuracy using ResNet50 and SVM.
Built a CNN-based gesture recognition web application for American Sign Language recognition.