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Data Analyst/ Business Analyst Resume

Mountain View, CA


  • Data analyst with 6+ years’ experience interpreting and analyzing large data sets for driving business solutions, building and evaluating analytic models, examining a range of disparate data sources, performing statistical analysis, creating reports/dashboards/graphs/storytelling to provide actionable insight for decision making.
  • Skilled in Statistical analysis, Quantitative analysis, predictive modelling and forecasting, hypothesis testing, data mining, data cleaning, data quality assessment data integration and validation, data modeling, ETL, data visualization
  • Proficient in MySQL(RDBMS, SQL server, PL SQL), Python(numpy, pandas, scikit - learn), R programming(ddply, ggplot2, random Forest), Core Java, Web scrapping, A/B Testing, Google analytics, web analytics, marketing analytics
  • Expertise in transforming business requirements into analytical models, design algorithms, develop reporting solutions that scales across massive volume of structured and unstructured data
  • Experience performing multi-function management and business analysis for various projects . Lead data analytics projects from requirement stage, scope analysis, developing models, deployment and support
  • Expertise in Advanced MS-Excel(Gsuite, sheets), PowerPoint, spreadsheets (Pivot table & Pivot Charts, Macros, VLOOKUP) Jupyter/ipython notebook, Version control software (GitHub, Bugzilla, Jira)
  • Knowledge of big data technologies, Hadoop, Hive, Map Reduce, NoSQL, JavaScript, Linux,HTML, CSS, AWS, Salesforce Customer Relationship Management(CRM) platform
  • Expertise in data visualization, developing Dashboards, Charts, Graphs and reports using Tableau
  • Detail oriented with excellent communication, problem solving, critical thinking and presentation skill
  • Passionate about machine learning, deep learning algorithms and artificial intelligence


Data analyst/ Business Analyst

Confidential, Mountain view, CA

  • Provided strategic, analytical and technical support for the Business Intelligence activities of the team
  • Used SQL, Python, Excel, and other tools to create reports and develop practical solutions to challenges for operations, engineering, and sales
  • Transformed existing standalone reporting into a coherent and extensible reporting workflow(ETL)
  • Wrote complex, efficient, and accurate SQL queries utilizing massive data sets
  • Set up foundational dashboards for executives to easily grasp trends and drill down to desired details
  • Achieved up to 90%-line reduction in existing core scripting while improving readability and accuracy
  • Automated the quarterly business review process to improve reliability and allow team leads more time to analyze trends instead of creating reports
  • Overhauled backup and snapshot processes to reduce redundancy without losing resiliency

Data analyst/Business Intelligence Analyst


  • Analyzed financial and marketing data to derive insights on conversions, retentions and financial performance
  • Partner with cross functional teams to solve exiting issues and build new features
  • Create monthly/quarterly/yearly report of impact analysis, Email marketing campaigns, revenue analysis, growth and opportunity analysis to deliver actionable insights
  • Create dynamic dashboards, reports, presentations to identify insights and present it to stake holders
  • Write SQL queries, procedures to automate the data modelling and cleaning
  • Build thoughtful and detailed models (such as regression analysis and classification using R/Python) to support business cases and to forecast the outcomes
  • Conducted quantitative analyses and ad-hoc analysis to roadmap decisions and briefed senior leadership, enabling them to improve products, provide user insights, consumer insights and marketing insights
  • Increased revenue impact by 15% through new strategic approach to focus on untouched areas with higher opportunities
  • Drive data accuracy and consistency across teams by identifying gaps in dashboards and data sources
  • Streamlined data pipeline process through process automation to increase efficiency
  • Leverage data to uncover new insights and help improve decision making for the business
  • Present periodic Dashboard reports on the current program, future opportunities, and client issues

Data analyst


  • Extracted data from multiple data source, write python (scrapy package, selenium) scripts to scrape data and images from ecommerce websites (web scraping)
  • Perform Data Profiling, Data pipelining, and Data Mining, validating and analyzing data (Exploratory analysis / Statistical analysis) and generate reports
  • ETL process to clean and load large data extracted from several websites (JSON/ CSV files) to the MYSQL server
  • Created reports and dashboards by connecting multiple data sources to help track user trends, behavior, engagement and performance.
  • Used python packages (Pandas, Numpy, Scikit learn) for feature engineering and machine learning models.
  • Used machine learning algorithms (Logistic regression as Baseline Model) to analyze the user demographics and trends.
  • A/B testing on customer data to test the new UI features added, measure the results, customer optimization.
  • Asses and implement advanced web analytics tracking, monitor KPI’s using Google analytics, create google analytics reports and dashboards
  • Set up virtual environment, write Unix/Linux shell script for system/process automation
  • Effectively communicate the finding to stakeholders and accelerate marketing goals

Data Analyst


  • Responsible for data extraction, Exploratory data analysis, understand the ‘Why’ behind data
  • Statistical analysis, Data analysis, anomaly/Outlier detection using R programming.
  • Developed Tableau dashboards & reports to show the analysis insights.
  • Effectively communicate the analysis outcome to team members and higher management.
  • Analyzed food preference and nutrition value using Logistic and linear regression model.
  • Led initiative to build regression model using R programming to classify and analyze food quality
  • Write SQL queries to update the database and extract the data for analysis
  • Dashboarding analytics, forecasting business goals and track KPIs

Software DevOps Engineer


  • Write automation scripts in python to automate the quality assurance of adobe.com application.
  • Write SQL queries to fetch customer data for verification
  • Reduced the test case failure by 80% with constant script and environment upgrades.
  • Responsible for budgeting, expense reporting, risk management, status reporting, and execution.
  • Developed dashboards to monitor the overall process and the progress.
  • Agile development process and scrum team meetings
  • Involved in data migration project to move data to AWS.
  • Knowledge of JavaScript, APIs and web services

Software Engineer


  • Executed roadmaps from inception to launch of record and replay tool for automation of mobile games
  • Actively managed the product development and other required regulatory compliances.
  • Performed extensive data driven competitive analysis.
  • Fixed defeats related to features and other areas.
  • HTML, Jquery and CSS object, Xpath to automate the quality assurance process
  • Performed data integrity, analysis and validity (MySQL).
  • Involved in setting virtual environment In Linux, write Linux script for process automation.

Software IT Analyst


  • Worked with global teams (insurance & healthcare domains) to develop software for process automation.
  • ETL process to store and retrieve data from SQL server, Database management, data warehouse
  • Troubleshoot test scripts, SQL queries, ETL jobs, data warehouse/data mart/data store models
  • Wrote and executed unit, system, integration and UAT scripts in a data warehouse projects
  • Performed testing on a data warehouse platform, including data integrity and data validation
  • Fostered Customer loyalty by ensuring that our customers fully utilize the value of our solutions and services
  • Delivered process management solutions for a leading insurance provider.
  • Managed client engagement services and solution implementations.
  • Collaborated with cross-functional teams to deliver products for customer lifecycle management.

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