Data Analyst Power Bi

GREESHMA SRI BIJJAM New Haven, CT, USA

Data Analyst +1-203-***-****

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PROFESSIONAL SUMMARY

Results-driven Data Analyst with 2 years of experience in leveraging data to drive strategic decision-making and operational efficiency. Proficient in Power BI, Tableau, SQL, and Python, with expertise in creating dynamic dashboards, optimizing ETL pipelines, and conducting predictive analytics. Delivered actionable insights from diverse datasets, resulting in revenue growth, cost reductions, and improved forecasting accuracy. Skilled collaborator with a proven track record in stakeholder communication, KPI development, and data visualization best practices to support data-driven organizational success. TECHNICAL SKILLS

Methodologies Software Development Life Cycle (SDLC), Agile/ Scrum, Waterfall Language & Database Python, SQL, NoSQL, MongoDB, Postgres, PL/SQL, MySQL, MSSQL, Azure SQL Database Python Packages Pandas, NumPy, Matplotlib, SciPy, Scikit-Learn, SeaBorn, PyTorch, TensorFlow, ggplot2 Cloud & IDES AWS, GCP, RStudio, PyCharm, Snowflake, Jupyter Notebook Data Analytics Skills Data Manipulation, Predictive Analysis, Data Cleaning, Data Mining, Data Visualization, Statistical Modeling, EDA, Data Modelling, Data Governance, A/B Testing, Cohort Analysis Tools Tableau, Power BI, ETL, SQLite, Cron Tasks, SharePoint, ServiceNow, Microsoft Excel, Visual Studio Data Tools, Talend, Microsoft office Suite, Jira, SSRS, SAS, Git, GitHub, Jenkins PROFESSIONAL EXPERIENCE

Data Analyst Bajaj Financial Services October 2021 – July 2023

• Analyzed and transformed structured, semi-structured, and unstructured datasets from 15+ sources, including SQL databases, APIs, and cloud platforms, to provide unified and actionable insights.

• Designed and developed 25+ dynamic Power BI dashboards with advanced features like drill-through filters and paginated reports, increasing decision-making efficiency.

• Conducted predictive and statistical analysis using DAX and Python, creating forecasting models that improved sales predictions by 15% and enhanced operational planning.

• Defined and monitored 20+ KPIs for operational efficiency and financial performance, resulting in a 10% reduction in costs and a 12% revenue increase through actionable recommendations.

• Optimized SQL queries and ETL pipelines, reducing data preparation time and query execution time by 35%, enabling real-time reporting and faster insights.

• Collaborated with stakeholders to translate business requirements into technical specifications, completing projects 20% ahead of schedule and improving cross-functional alignment.

• Documented data models and pipelines conducted detailed presentations of insights, and implemented best practices in data visualization, ensuring clarity and long-term usability. EDUCATION

Master of Science in Information Sciences August 2023 – May 2025 University of New Haven New Haven, CT, USA

Bachelor of Education in Computer Science July 2019 – May 2023 Lovely Professional University Phagwara, Punjab, India PROJECTS

CAREER TRACK PROGRESS DASHBOARD January 2025 – May 2025 Tools/Tech: SQL, Tableau, Python, Logistic Regression, Git, Data Quality, KPI Design

• Optimized complex SQL queries on over 1 million rows using CTEs, indexing, and window functions, reducing dashboard refresh time by 45% and ensuring consistent daily pipeline execution for enrolment and exam datasets.

• Built a logistic regression model (AUC: 0.82) to predict certificate completion likelihood; integrated the output into Tableau to enable targeted faculty interventions and early support for at-risk students.

• Designed an interactive Tableau dashboard with dynamic KPIs, parameterized what-if analysis, and drill-through filters; uncovered key insights like a 22% dropout spike between Courses 5–6, resulting in a 9-point improvement in next cohort performance after intervention.

• Led cross-functional collaboration with curriculum leadership and TAs in an Agile sprint cycle, implemented automated data validation scripts and Tableau Data Quality Warnings, and conducted faculty workshops that boosted dashboard adoption to 100% while reducing ad-hoc report requests by 80%

COVID-19 Testing & Positivity Analysis – Global Dataset August 2024 – December 2024 Tools/Tech: R, ggplot2, dplyr, readr, Functional Programming, EDA

• Cleaned and transformed 500K+ WHO records using readr, dplyr, and tibble, ensuring 100% data integrity through column validation and NA handling across 180 countries.

• Conducted exploratory analysis to derive KPIs like total tests, positivity rate, and confirmed cases; identified >25% positivity clusters in high-testing nations, signalling possible under-reporting.

• Visualized findings using ggplot2, delivered a 10-minute presentation, and published a reproducible R script with README.md, demonstrating best practices in data governance and functional programming.

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