Sr. Data Analyst

Dallas/Fort Worth, TX

Opportunity Details

ContractBusiness Analysis

Dallas/Fort Worth, TX
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• Strong in SAS, SQL

• Strong Analytics Background with good exposure to model development, reporting tools (Tableau, PowerBI)

• Strong in Advance-Excel, preferably VBA

• Strong in basic Accounting and Finance 

• Patterned and Trend Analysis
• Experience in Alteryx, Python/R
• SQL, Spark SQL, Oracle, Microsoft Azure Databricks
• 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 Techniques (Probability distributions, Confidence Intervals, Statistical Inference, Average, Median, Time Series, Pre and Post data analysis)
• 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.

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