4 years of experience in Analytics (handson) Experience in business requirements gathering Ability to problem solve and break down complex problem into solvable pieces Ability to deliver quick and accurate results for each analysis/task Good communication skills Experienced in data management, data analysis, data extraction

KEY RESPONSIBILITES AND DUTIES Performing data cleaning, data modeling, data crunching and in-depth data analysis on KPI s and optimization of subroutine analytics of communications and data mining methodologies. Develop visual, interactive reports using Tableau, Power BI for effective prediction and understanding of data analysis trends and creating automated data analysis workflows using Alteryx designer. Supporting the Director of Business Planning Analytics through both ad-hoc and project work by analyzing sales data for new opportunities, providing customize reporting and recommendations in support to on-going business decisions and, conducting quantitative analysis including but not limited to ROI, trending, identification and assessment of opportunities and risk, forecasting, regressions, correlation, cannibalization and probability modeling. Utilizing Excel advance techniques like Pivot Table, V-Lookup H-Lookup for mining data and performing analysis on various sources and summarizing data. Implementing statistical algorithms such as Linear, Logistic Regression, and Clustering for segmentation's, Time series model (ARIMA), Factor analysis for building correlation, prediction and visualization of the model. Performing A/B testing and target vs control analysis and profiling, market basket analysis to identify trends and analyze customer purchase behavior. Working on Waterfall as well as Agile environment including the Scrum process. Familiarity with statistical programming languages and packages (SAS, SPSS, R, Python) Utilizing the knowledge of quantitative analytics, data mining, statistics and data visualization to present insights to the senior management to facilitate in strategic decision making. Working on various reporting objects like Dimensions, Measures, Filters, Calculated Fields, transformations, parameters, conditional formatting, DAX queries, Interactions etc. in Power BI. Performing Dimensional Data Modeling, Process Modeling for Data Warehouse /Data Mart design, identifying Facts and Dimensions, the creation of cubes, Star Schema, and Snowflake Schema. Performing exploratory data analysis and data investigation using Alteryx, SQL and Python. Data management and analyses to enable customer support teams using Excel, Google Sheets, Tableau, Power BI and SQL Performing descriptive, diagnostic, inferential, prescriptive, and predictive analysis of data. Extensively working on the creation of customer segmentation, profiling and defining customer purchase patterns using existing customer demographic/transactional data. Creating engagement tracking dashboards and funnel reports for the mobile app to assist the Product development team through Mix-panel and New Relic. Performing A/B testing Communicating insights from data analysis and influencing change and generating insights and recommendations and presenting these to the senior management. Performing descriptive, diagnostic, inferential, prescriptive, and predictive analysis of data. Extensively working on the creation of customer segmentation, profiling, and defining customer purchase patterns using existing customer demographical/transactional data. Verification of various offers/promotions set by the business teams with pre/post transactional data. Extracting data from various sources (Oracle, Databricks, MongoDB) using DB queries, Designing and implementing dashboards based on transformed data. MUST HAVE SPECIFIC KNOWLEDGE AND SKILLS

• Strong in SQL, Power BI, Data Analyis and Statistical concepts
• Strong Analytics Background with good exposure to reporting tools (PowerBI or Tableau)
• Exposure to Alteryx, Python or R
• Strong in Excel (pivots, VLOOKUP s, basic formulae), Power Point (charts, graphs)
• Analytics concepts: Test and Control methodology (Sales data analysis, Loyalty Program Analytics, Customer segmentation, Descriptive analysis, Cohort Analysis, Offers/Promotions data trend analysis (coupons, bonus offers, rewards, member offers)
• Statistical Concepts (Probability distributions, Confidence Intervals, Statistical Inference, Mean, Mode, Median, Hypothesis Tests)