Ambareesh Bandaru
Ramp
Clarksburg,MD
6
years of professional experience
Results-driven Data Analyst with 4+ years of experience transforming complex datasets into actionable insights using Python, SQL, and machine learning. Proven track record improving data accuracy by 25%, boosting operational efficiency by 18%, and enhancing forecasting accuracy by 20%. Experienced in scalable ETL pipelines, A/B testing, predictive modeling, and executive dashboards across fintech and banking. Skilled at translating ambiguous business problems into rigorous data-driven solutions using GCP/BigQuery, AWS, Spark, Tableau, and Power BI.
Work History
Data Analyst
1 Year 2 Months- Built end-to-end predictive analytics solutions using Python, Scikit-learn, and TensorFlow to model user engagement patterns, driving a 15% improvement in product activation rates.
- Designed scalable data pipelines using Apache Spark and Airflow processing 10M+ daily events to power real-time dashboards for product and growth teams.
- Led A/B experimentation framework across 20+ product experiments, applying hypothesis testing and power analysis to ensure statistically reliable outcomes.
- Developed NLP models to analyze user feedback signals, surfacing friction points that informed roadmap decisions and reduced churn by an estimated 12%.
- Built self-serve Tableau/Looker dashboards partnering with engineering and PM teams, reducing ad-hoc reporting requests by 30%.
Data Analyst
1 Year 11 Months- Automated ETL workflows in Python and SQL across banking, operations, and risk, cutting manual reporting time by 40% and improving data accuracy by 25%.
- Built Tableau and Power BI dashboards tracking 30+ KPIs for senior stakeholders, enabling faster decision-making across risk and operational functions.
- Developed time series forecasting models to predict transaction volumes and flag anomalies, improving forecasting accuracy by 20%.
- Partnered with risk, compliance, and engineering to standardize data definitions and resolve data quality issues, boosting operational efficiency by 18%.
Data Science Intern
8 Months- Built an employee attrition predictor using Logistic Regression, Decision Trees, SVM, and XGBoost; optimized via RandomizedSearchCV achieving 87% accuracy.
- Deployed the final model as a Flask web application integrated with enterprise HR systems, enabling proactive identification of at-risk employees.
Education
M.S. - Data Science
B.Tech - Electrical, Electronics & Communications Engineering
Skills
Languages & Query: Python (Pandas
NumPy
Scikit-learn
TensorFlow
XGBoost)
SQL (BigQuery
PostgreSQL)
R
ML & Analytics: Machine Learning
Predictive Modeling
NLP
A/B Testing
Statistical Analysis
Time Series Forecasting
Data Engineering: ETL Pipeline Design
Apache Spark
Airflow
Data Warehousing
dbt
REST APIs
Visualization & Cloud: Tableau
Power BI
Looker | AWS (S3
Redshift)
GCP (BigQuery
Dataflow)
Azure
Docker
Git
Timeline
Data Analyst
Ramp
06.2025 - CurrentRead More
Data Analyst
Goldman Sachs
07.2021 - 06.2023Read More
Data Science Intern
IICL
07.2020 - 03.2021Read More
Vignan’s Lara Institute of Technology & Science
B.Tech from Electrical, Electronics & Communications Engineering
Read More
Florida Atlantic University
M.S. from Data Science
Read More