Machine Learning Power Bi

DHARANI KOUSALYA PENTA

667-***-**** • *********************@*****.*** • LinkedIn • GitHub

Results-driven Data and Business Analyst with 3+ years of experience in translating complex data into actionable insights using Python (Pandas, NumPy, Scikit-learn), SQL, Power BI, and Tableau. Expert in machine learning (BERT, GPT, NLP), A/B testing, and KPI dashboards, driving data-backed decisions. Proven ability to optimize business strategies through predictive modeling, clustering, and advanced analytics, enhancing engagement, retention, and operational efficiency. Passionate about leveraging AI to solve real-world challenges. SKILLS

Programming and Data Analysis: Python (Pandas, NumPy, SciPy, statsmodels, Matplotlib, Seaborn), SQL (PostgreSQL, SQL Server), R Machine Learning: Scikit-learn, TensorFlow, Logistic Regression, Decision Trees, Random Forests, Naive Bayes, NLP, Forecasting, Clustering (k-means, hierarchical), BERT, GPT, Named Entity Recognition (NER) Data Visualization: Power BI, Tableau, Excel (DAX, Power Query, Pivot Tables) Tools and Platforms: Jupyter Notebook, Google Colab, Git, MATLAB Cloud: AWS, Azure

PROFESSIONAL EXPERIENCE

Data Analyst Intern Apr 2025 – Present

SportsMedia Inc.

Delivered actionable insights from exploratory data analysis on cross-platform engagement with Python and SQL, influencing feature roadmap and retention strategy.

Created KPI dashboards in Power BI using SQL, enabling stakeholders to track engagement, retention, and campaign outcomes with self-serve analytics workflows.

Collaborated on A/B testing design and analysis, utilizing Python libraries (statsmodels, scipy) to assess test validity and drive data-backed decisions on feature rollout.

Identified significant user churn indicators via multivariate analysis and logistic regression, guiding the design of targeted interventions for at-risk audience segments.

Utilized clustering techniques (k-means, hierarchical) to segment user base by interaction patterns, supporting content personalization efforts across digital platforms. Data Analyst Intern Feb 2025 – Present

Trulogik

Leveraged Power BI and SQL Server to build real-time dashboards that enhanced visibility into recruitment KPIs and enabled HR leaders to track performance.

Interpreted historical applicant data trends across multiple channels to guide strategic decisions on sourcing efficiency, engagement, and candidate quality metrics.

Participated in weekly cross-functional analytics reviews with HR stakeholders, translating complex hiring data into clear, actionable insights aligned with KPIs.

Applied cohort analysis to monitor long-term performance of candidate sources and reported findings to improve recruiter focus and channel prioritization decisions.

Created structured narrative reports that contextualized hiring patterns through visual analytics, enabling better decision-making for future workforce planning. Junior Data Analyst Sep 2022 – July 2023

Cognizant

Delivered executive-ready Power BI dashboards tracking KPI trends to support weekly planning sessions with real-time insights and cross-functional collaboration.

Extracted insights from relational databases using complex SQL queries with CTEs and joins, optimizing data retrieval for recurring performance analysis reporting.

Analyzed operational inefficiencies by performing in-depth exploratory data analysis (EDA) with Python libraries, enabling business stakeholders to refine workflows.

Collaborated with business managers to identify underperforming areas and visualized root causes using Tableau, driving actionable conversations during reviews.

Conducted error trend investigations through SAP system logs and summarized patterns in interactive charts, supporting reduction strategies for recurring issues. Data Analytics Intern Feb 2022 – Aug 2022

Cognizant

Built dashboards and reports using Tableau and Power BI, empowering QA managers with insights that supported timely interventions during release testing cycles.

Conducted in-depth trend analysis using Python libraries such as pandas and SciPy to identify failure patterns across test cycles and improve defect detection strategy.

Developed Excel-based reporting templates with nested formulas and pivot logic to standardize KPI reporting, enhancing visibility into QA throughput metrics.

Collaborated with business analysts to define success criteria for UAT scenarios, enabling precise tracking of test coverage gaps and improving stakeholder confidence. PROJECTS

Power BI Sales Dashboard, Tools: Power BI, Power Query, DAX, Excel

Designed a dynamic dashboard to analyze revenue, market share, sales region-wise, empowering executives with better visibility across product categories.

Utilized Power Query for live data refresh and optimized DAX measures, reducing insight delivery lag and enabling rapid actions that improved quarterly decisions. HR Analytics Dashboard, Tools: Tableau, Excel

Developed interactive dashboards analyzing attrition, satisfaction, and tenure, allowing HR teams to monitor department-level employee performance indicators.

Leveraged visualization to dissect turnover drivers, enabling HR leaders to act on trends through targeted retention efforts that strengthened organizational stability. AI-Based Legal Document Summarization, Tools: Python, BERT, GPT, Named Entity Recognition (NER), ROUGE/BLEU

Built a Transformer-based pipeline using BERT and GPT models to compress Supreme Court rulings, streamlining lengthy documents into searchable summaries.

Integrated NER and evaluated results with ROUGE/BLEU scores, accelerating document triage by enriching legal records with metadata for faster legal referencing. Uber Data Analysis, Tools: Python, Pandas, Seaborn, Matplotlib

Analyzed over 1.5 million ride entries to extract trends in peak demand, location-based usage, and seasonality, supporting geo-optimized resource allocation.

Visualized usage dynamics and identified service gaps with Seaborn and Matplotlib, guiding enhancements that boosted ride availability during critical time windows. Chronic Kidney Disease Prediction, Tools: Python, Scikit-learn, Pandas, Matplotlib

Developed a Random Forest classifier to achieve high diagnostic precision for CKD using SMOTE-enhanced data and feature engineering on medical test indicators.

Enabled early detection by achieving reliable predictions, reducing diagnostic delays and supporting preventive healthcare intervention through model integration. EDUCATION

University of Maryland, Baltimore County (UMBC)Aug 2023 – May 2025 Master of Professional Studies in Data Science, CGPA: 4.0/4.0

Relevant Coursework: Introduction to Data Science, Introduction to Data Analysis and Machine Learning, Platforms for Big Data Processing, Data Management, Ethical and Legal Issues in Data Science, Capstone in Data Science, Leadership in Data Science ADDITIONAL EXPERIENCE

Lead Tutor – Reach Together Tutoring Program Jan 2025 – May 2025

Led a tutor team and deployed dashboards to track progress, significantly improving student performance. Math Tutor – Reach Together Tutoring Program June 2024 – Jan 2025

Provided 1:1 tutoring and tracked academic progress of 100+ students, increasing test scores by 20%.

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