Knowledge of working across multiple data types and files like flat files, RDBMS files multiple data platforms (SQL Server, Teradata, Hadoop, Spark) on premise or on the cloud Understanding of consumer businesses such as Retail, CPG or Telecom Experience in handling client calls and working independently with clients Experience in managing, cleaning and analyzing large datasets using tools like Python, R or SAS Experience in using multiple advanced analytics techniques or machine learning algorithms 8-10 years of relevant advanced analytics experience in Marketing, CRM, Pricing in either Retail, or CPG industries. Excellent communication skills, both written and verbal Desire to work in a fast paced, challenging environment where you need to push yourself all the time Superior problem solving abilities and strong analytical thinking Be a part of deliverable discussions with clients over telephonic calls, and guide the project team on the next steps and way forward Most Important Requirements:
Act as client lead and maintain client relationship make independent key decisions related to client management Discuss queries/certain sections of deliverable report over client calls or video conferences Client Management Be able to take client calls relatively independently, and interact with onsite leads (if applicable) on a daily basis Be able to succinctly visualize the findings through a PPT, a BI dashboard (Tableau, Qlikview, etc.) and highlight the key takeaways from a business perspective Interpret the output in context of the client’s business and industry to identify trends and actionable insights
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Conduct sanity checks of the analysis output based on reasoning and common sense, and be able to do a rigorous self QC, as well as of the work assigned to junior analysts to ensure an error free output
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Explore and implement various statistical and analytical techniques (including machine learning) like linear/non-linear Regression, Decision Trees, Segmentation, time series forecasting as well as machine learning algorithms like Random Forest, SVM, ANN, etc. Organize/Prepare/Manage data and conduct quality checks to ensure that the analysis dataset is ready Be able to translate the client objectives / analytical plan into clear deliverables with associated priorities and constraints
Understand the client objectives, and work with the Project Lead (PL) to design the analytical solution/framework.
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