Data Analyst Power Bi

SKILLS

EXPERIENCE

CERTIFICATIONS ACHIEVEMENTS

Swapnali Sangale

Data Analyst

*****************@*****.***

Pune 876-***-**** LinkedIn

1+ year of experience as a Data analyst skilled in SQL, Python, Power BI, and machine learning, with experience optimizing customer segmentation using K-Means clustering to enhance targeted marketing, improve engagement by 25%, and deliver actionable insights for data-driven decision-making and business growth. Core Skills: Python, SQL, PySpark, R programming

Tools: MySQL, Excel, Power BI, Snowflake, Visual Studio Code, Databricks, Streamlit, AWS Technologies: AI/ML, Predictive Analytics, Deep Learning, Statistics, Regression, Classification, NLP, Time Series Forecasting, ETL, Apache Airflow

Libraries/Frameworks: Pandas, NumPy, Scikit-Learn, Matplotlib, Statsmodels CLOUDLEAD TECHNOLOGIES Data Analyst (Feb 24 – Present)

• Built and optimized SQL pipelines for lead targeting and segmentation, enabling marketing teams to identify high- value prospects effectively.

• Improved conversion accuracy across multiple B2B outreach campaigns by streamlining data workflows and refining targeting strategies.

• Automated lead scoring, data enrichment, and campaign readiness workflows using Python and Excel, enhancing sales operations efficiency.

• Designed and maintained interactive Power BI dashboards to monitor outreach KPIs and sales funnel metrics in real-time.

Campaign Performance Dashboard using Power BI

• Developed a Power BI dashboard integrated with SQL views and scheduled data pulls, providing sales teams with real-time access to live metrics for better lead prioritization.

• Cleaned and transformed large, multi-source datasets using Python scripts to enhance data quality and improve precision in targeting high value leads for marketing campaigns.

• Utilized Excel alongside Python to support continuous campaign refinement by integrating diverse data sources, enabling more effective outreach and improving overall lead targeting accuracy. Optimized Customer Segmentation using Clustering

• Developed customer segmentation model using K-Means Clustering and PCA (Principal Component Analysis) to categorize customer data, improving targeted marketing and increasing engagement by 25%.

• Identified high-potential customer segments based on demographics and spending behaviour for cross-selling, leading to increased uptake of relevant financial products and services.

• Analysed transaction behaviour and account activity to provide personalized product recommendations, boosting customer retention across key segments.

M.Sc. in Computational Mathematics (2022) B.Sc. in Mathematics (2020) NMU Jalgaon University NMU Jalgaon University

CGPA: 9.21 CGPA: 9.67

• Machine Learning Engineer from Symbiosis • 1st in B.Sc. (Math)

• Master of Data Science from 3RI Technologies • IIT JAM-2021 qualified (AIR – 748) PROJECTS

EDUCATION

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