Power Bi Data Analyst

PARTHIKA BATTALA

+1-630-***-**** ***************@*****.***

LinkedIn GitHub Portfolio

SKILLS

Technical Skills

Power BI, Tableau, Excel, Python (Pandas, Matplotlib, Seaborn), SQL, R, Jupyter, Streamlit, Git, Power Query, Google Sheets, ETL Processes

Data Science & Analytics

Predictive modeling, A/B testing, Statistical Analysis, Data validation, Data Modeling, EDA, Financial Reporting, BI Reporting, Agile, JIRA,

Dashboard development, Business intelligence tools, Qualitative analysis

Cloud & Platforms

AWS (S3, Athena, Redshift), Google Cloud (BigQuery), Gen AI

Soft Skills

Analytical thinking, problem solving, critical thinking, collaboration, communication, cross-functional stakeholder reporting

PROFESSIONAL EXPERIENCE

Data Analyst Intern Wayfair Boston, USA

Tools: Python, SQL, Pandas, Google Cloud (BigQuery, Cloud Storage), Power BI, Excel, SciPy, Google Cloud IAM Apr. 2024 – Oct. 2024

• Automated financial reporting pipelines and dashboards, reducing manual effort by 40% while ensuring data security.

• Applied anomaly detection to key financial metrics, enhancing data accuracy and preventing errors.

• Collaborated with finance and IT to build forecasting models that supported strategic decision-making.

Data Analyst Intern Cognizant Bengaluru, India

Tools: Power BI, Python, SQL, Excel May 2022 – Jun. 2023

• Automated healthcare KPI reporting using Power BI and Python, cutting manual data prep time by 40% and boosting report accuracy and

speed.

• Developed and optimized SQL queries to extract and process data from multiple clinical databases, ensuring reliable weekly reports.

• Implemented data validation and cleansing workflows with Python and Excel, reducing data errors by 30% and enhancing insight quality.

• Delivered weekly analytics reports to internal teams and supported client dashboard reviews, improving healthcare project outcomes.

Data Insights Intern ZettaMine Labs Hyderabad, India

Tools: Excel, SQL, Power BI, Python Nov. 2021 – Apr. 2022

• Designed and implemented dashboards to present key business metrics, enabling clients to make faster, data-driven decisions.

• Cleaned and analyzed large datasets using Python and SQL, uncovering trends that improved forecasting accuracy by 15%.

• Automated data consolidation and reporting, cutting report generation time by 30% and boosting team collaboration.

PROJECTS

AI-Powered Pneumonia Detection with Explainable Deep Learning [Python, PyTorch, TensorFlow, Grad-CAM]

• Developed a deep learning model using pretrained CNNs (ResNet18, EfficientNet-B0, DenseNet121) to classify pneumonia from chest X-rays.

• Addressed class imbalance with weighted sampling to improve recall and reduce false negatives critical for healthcare.

• Applied Grad-CAM for visual interpretability, enhancing transparency by highlighting important regions in X-ray images.

• Achieved 88.3% accuracy and 0.89 F1-score with ResNet18, demonstrating robust performance for diagnostic support.

Sales Forecasting Model with Time Series Analysis [Python, Pandas, Prophet, Matplotlib]

• Developed and deployed a time series forecasting model using Facebook Prophet to accurately predict monthly sales for a retail client,

improving demand planning.

• Processed multi-year sales data by handling missing values and modeling seasonal and holiday effects to improve forecast accuracy.

• Delivered forecasts with MAPE below 8%, supporting optimized inventory management and revenue growth.

Customer A/B Testing Dashboard [Python, Streamlit, SciPy, Pandas]

• Built an interactive web app that automated statistical testing (t-tests, chi-square) on marketing experiment data, simplifying analysis for

non-technical users.

• Enhanced the dashboard with Tableau visualizations to improve user experience and data exploration.

• Enabled data-driven marketing decisions that increased campaign targeting accuracy and conversion rates by 15% in simulated tests.

Social Media Sentiment Analyzer [Python, NLTK, Scikit-learn, Power BI, Data Analysis]

• Created an NLP pipeline using VADER and Logistic Regression to classify Twitter sentiment on brand mentions with 85% accuracy.

• Designed interactive Power BI dashboards to track sentiment trends and key discussion topics over time.

• Delivered actionable insights that helped marketing teams improve reputation management and respond effectively to customer

feedback.

EDUCATION

Master of Science in Data Science, Lewis University Aug. 2023 - May 2025 Romeoville, IL

Relevant Coursework: Relational Databases Design, Data Warehousing & SQL, Data Mining, Cloud Analytics, Predictive Analytics, Big

Data, Machine Learning, Statistical Modeling, Applications of AI, Data Visualization, Probability and Statistics.

B. Tech in Electronics and Communication Aug. 2019 - May 2023 Hyderabad, India

Anurag Group of Institutions

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