· Spend time with client team members, Agile coaches and internal teams to understand their needs, problems, and wants.

· Developed Linear Regression/Multiple Linear Regression, Predictive Modeling for workforce analytics team using Python Based Machine Learning techniques and makes sure what external factors influencing what causes the failures for the product not getting success in the market

· Connecting to different network across organization and pulling the information, performing business calculations across different line of business through python pandas/numpy/matplotlib/Scikit and other libraries.

· Manage and work from a prioritized backlog.

· Spend time understanding the data and pulling data from a number of sources.

· Analyze and document business data requirements and create functional/technical design documents and related documentation.

· Design and develop conceptual, logical, and physical level data models (both relational and dimensional) for data marts.

· Additional responsibilities include source system analysis (understanding schemas, joins), data profiling of complex, under-documented systems, and source to target mapping (Physical to Logical, Logical to Physical).

· Data mapping, transformation and integration of relational/dimensional data models.

· Develop metrics dashboards in Qlik Sense.

· Connecting the network across the organization

· Migration report from SaS code logic to Qlik Script.

· Integration of python with Qlik sense to do the forecasting model.

· Migration of the PL/SQL procedure report to Qlik Script.

· Develop strategies and designs for dashboard.

· Performed and documented data analysis, data validation, data mapping/design, by accessing multiple sources, specifically data residing in data warehouses.

· Analyzed Key Performance Indicators (KPI's) with help of Tableau reports.

· Blended data from variety of data sources while creating tableau reports.

· Scheduled data refresh on Tableau server for daily, weekly and monthly increments based on business change to ensure that views and dashboards were displaying the changed data accurately and sent those to production after editing.

· Developed dashboard reports to understand bids, conversion, profit, and demographics metrics.

· Developed visualization reports for daily, weekly, monthly and yearly conversion and comparison analysis utilizing Tableau.

· Resolved data quality issues by performing root cause analyses, mapping data sources, and improving user workflows.

· Performed data analytics relevant to investigation issues and worked by integrating tableau with R programming.

· Tuned complex workbooks and large datasets for optimal performance and maintainability.

· Worked with extracts, live datasets, and managing access privileges.

· Developed analytical and business models to estimate an impact of different scenarios.

· Translated analytical findings into clear, easily understandable, actionable insights that drive strong business strategy.

· Analyzed key metrics, identify key trends and prepare reports and presentations for senior executives and other key management representatives. We represented this information in the form of python based machine learning techniques.

· Standardized data collection by developing methods for database design and validation where we used Spark Scala framework.

· Created interactive dashboards in Tableau Desktop and published them to Tableau server which allowed story telling with quick filters to retrieve on demand information with just click of a button.

· Designed and implemented advanced Tableau visualizations using action filters, user filters and Level-of-Detail (LOD) expressions.

· Created tableau data sources utilizing custom SQL and deploy them once the data source data got fully validated.

· Developed visualization reports for daily, weekly, monthly and yearly conversion and comparison analysis utilizing Tableau Desktop.

· Scheduled data refresh on Tableau server for daily, weekly and monthly increments based on business change to ensure that views and dashboards were displaying the changed data accurately and sent those to production after editing.

· Performed ad-hoc analysis as needed using internal and external data sets.

· Optimized user experience by analyzing behaviors, predicting churn, segmenting users, defining metrics, and designing tests.

· Analyzed key drivers of customer behavior and built models to predict customer retention.

· Analyzed traffic patterns to draw inferences from data behavior.

· Developed key performance indicators to track call center agent productivity and activity.

· Programmatic search and social campaigns by analyzing performance, optimizing bids, and implementing client deliverables.

· Managed data operations by developing SQL queries, and investigating data quality issues.

· Prepared Quality Score Metrics and Campaign analysis from backend data provided.

· Primary responsibility was to develop executive level dashboards in Tableau.

· Created tableau data sources with help of custom SQL and deployed them once data source data got fully validated.

· Created and published Tableau reports as per requirements from the business team.

· Scheduled data refresh on Tableau server for daily, weekly and monthly increments based on business change to ensure that views and dashboards were displaying the changed data accurately and sent those to production after editing.

· Worked closely with various teams such as clients and media facing business team, BigData + Tableau + Oracle + UNIX admin teams and Java based Development + QA team to get data.

· Demonstrated progressive changes to stakeholders at regular intervals.

· Helped a product team to improve products by identifying and defining key marketing performance metrics.

· Optimize user experience by analyzing behaviors, predicting churn, segmenting users, defining metrics, and designing tests.

· Analyzed data quantitatively and qualitatively with tools like Tableau and Oracle BRIO.

· Performed monthly/weekly revenue scorecards and revenue projections.

Used advanced Microsoft Excel for creating Macros, Pivot Table, VLookups and excel functions.

Involved in the below mentioned product developments:

1. LeadGen Platform

QuinStreet has built a platform which is responsible for driving traffic to LeadGen sites developed by QS. The platform is also responsible to deliver leads submitted by online users to our clients using Web Services, Email and other distribution channels

2. XEngine Platform

XEngine is a platform designed by QS for launching portals. It features the ability to share leads across multiple clients. It will be used for both micro-sites, multi-lead sites and directory sites. List of verticals supported by XEngine include Education, Mortgage, Home Services, Medical and Insurance, and B2B. Products developed under XEngine platform include SiteGenie, Client Services and Publisher Services.

A. SiteGenie is intended to provide a set of administrative tools to help quickly launch QuinStreet clients and manage existing clients. Integrated SalesForce with SiteGenie to allow Account managers manage prospects and business opportunities and can also generate leadgen sites on fly.

B. Publisher Services allows Publishers to enroll with QuinStreet network and view leads they posted/collected on behalf of QuinStreet.

C. Agent Platform allows launching of the agents and intended to allow agents to view their leads, configures their billing data (prepay, postpay, credit card details), lead criteria details, lead notifications and view invoice data.

Contact Center

3. Contact Centre system is an initiative to boost up leads conversion which are captured by platform system and leads bought from publishers. It’s an integration of QuinStreet Platform with 3rd party telephony system, where the leads are transferred from QuinStreet Platform to Telephony System in real time.