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Data Analyst Resume


  • Reliable, hard - working, problem-solving professional with high level of communicational skills and extensive knowledge of BA and BI field: SQL, TSQL, SQL Server, MS Excel, Oracle, Python, Azure, Data Science and Machine Learning theory: Classification, Regression; Data Visualization tools (Power BI, Tableau), ETL process.
  • Looking for an employment in the BA and BI field to use the great job experience and combine existing skills with new activities using strong potential that consequently lead to sustainable career and professional growth.
  • 3+ years of professional experience in Business Analytics and Business Intelligence field: building reports, responsible for monitoring and evaluating business process performance using BI Tools; weak points detection and presenting solutions that led to KPI improvement.
  • Experienced in Data validation, Data - Cleansing and Normalization processes.
  • Experienced in data manipulation process: using MS Excel and SQL Server for writing complex SQL queries using derived tables, CTEs, views, multiple joins, sub-queries.
  • Performed Data Analysis and Data Validation by writing complex SQL queries.
  • Worked on high professional level with superior management from Marketing, Production, Finance & Accounting, Supply Chain (Purchasing and Logistics), Internal Audit Departments and discussed analysis needs and requirements with them.
  • Attended daily standup meetings for discussion focal points, tasks performance status, updates.
  • Experience in data retrieval process by using SQL Server and SSIS.
  • Professional in Business Intelligence tool: Power BI, at that great skills with operating in Tableau.
  • Perfect understanding of Visualization Techniques, which were used for best presentation of summary reports, detailed reports, ad-hoc reports.
  • Using Power BI Drill Through, Drill Down functions and Hierarchies for detailed report developing.
  • Extensive knowledge in data manipulation techniques within Power BI: using Power Query and dashboard filtering functions: visual, page and report-level filters, adding constant and average lines (dashboards); fields/columns splitting, filtering, data type changing, copying, deleting (Power Query).
  • Highly proficient in design and development of various types of reports on Power BI Visualizations section: bar graphs, scatter plots, pie-charts, maps, donuts, bubbles, matrix, table mode, etc.
  • Created summary, detail, KPI, ad-hoc reports using DAX Functions.
  • Proficient in writing DAX formula for creating Measures, Calculated Columns, execution of various calculations and other data manipulation.
  • Performance of EDA (Exploratory Data Analysis) in Python using Jupyter Hub: analyzing data aiming to perform statistical analysis, validate data main characteristics.
  • Have good knowledge in creating Visualizations for better understanding the correlation between the features in dataset, for better representation of focal values activity and other information using Matplotlib and Seaborn.
  • Intensively operated Python using different Libraries, such as Pandas, NumPy, Math, Matplotlib, Seaborn, ScikitLearn.
  • Experienced in using Python ML (Machine Learning) and Business Science processes: Data Preparation, Feature Engineering, Model Building, Model Performance Evaluation.
  • Preprocessed raw data by different techniques: handling nulls, outliers, data standardization, categorical data encoding.
  • Experienced in feature selection for preparation the dataset for prediction.
  • Executed supervised machine learning models such as Linear Regression, Logistic Regression, Decision Tree, Random Forest, KNN for categorical and continuous data (Classification & Regression) to predict classes and values using Scikit-Learn Library.
  • Used unsupervised machine learning models such as K-Means clustering.
  • Evaluated the performance of Machine Learning Models (MLM) by checking accuracy and mean absolute error using Confusion Matrix (Categorical) and R-Squared (Continuous).
  • Familiar with process of deploying machine learning models to Azure ML cloud.
  • Extensive experience in ETL process (Extract, Transfer and Load) (ETL) using MS SQL Server Integration Services (SSIS).
  • Excellent leadership, problem-solving and communicational skills, able to work independently and within a team, ready for constant learning, open for great challenges, stress-resistant, detail-oriented, determined.



Data Analyst


  • Supported management team with reports generation and analysis using reporting and visualization BI tool: Power BI.
  • Created Drilldown-Reports, Summary Reports, Parameterized Reports, Ad-hoc Reports using Power BI by analyzing customer’s satisfaction, financial parameters, revenue, expenses, etc.
  • Used Python (Jupyter Hub) for data cleansing, exploratory data analysis, statistical analysis: to understand trends and its customers.
  • Performed Deep Dive Analytics and developed Customer Dive Dashboards to monitor buying patterns of the customers which helped the marketing department to retain the existing customers and bring in new customers to the platform.
  • Based on Customer Satisfaction data created Deep Dive Dashboard for the Product department to help manage psychic performance and increase productivity.
  • Created customer Churn Analysis Report and used predictive analysis techniques to predict customers who may drop out and created flags for the marketing department to send them offers to retain them.
  • Deeply analyzed customer satisfaction field, performed the reports to inspect customer mood affecting factors, created reports for monitoring the rating correlation with revenue, profit and losses.
  • Created Financial Reports highlighting areas of Sales growth, Sales trends, Direct Expenses and Profitability to help the finance department take proper decisions.
  • Used Power BI tools and Dax functions to develop Hierarchical dimensions, Measures, Calculated Columns, KPI, Filters and Aggregations.
  • Generated joins and sub-queries in SQL to retrieve the required fields and records from multiple tables.
  • Expertise in data mining and data cleaning.
  • Professional in detecting weak points in data.
  • Presenting reports including the list of accurate solutions.
  • Used Common Table Expressions (CTE’s), Constraints, and Complex queries to fetch the data from different servers and datasets.
  • Set Row Level Security to keep customers and payments data secure and confidential.
  • Attended daily/weekly status meetings, project review meetings, and walkthroughs with project managers and leads.

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