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- Strong in SAS, SQL• Strong Analytics Background with good exposure to model development, reporting tools (Tableau, PowerBI)• Experience working with Pharma industry data is highly preferred. • Patterned and Trend Analysis
- Experience in Python/R
- SQL, Spark SQL, Oracle, Microsoft Azure Databricks
- 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.
- 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.
- Working on Waterfall as well as Agile environment including the Scrum process.
- Familiarity with statistical programming languages and packages (SAS, R, Python)
- Utilizing the knowledge of quantitative analytics, data mining, statistics and data visualization to
- Working on various reporting objects like Dimensions, Measures, Filters, Calculated Fields,
- Performing Dimensional Data Modeling, Process Modeling for Data Warehouse /Data Mart design,
- 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