Specifically, Assistant Managers should –
Understand the client objectives, and work with the Project Lead (PL) to design the analytical
solution/framework. Be able to translate the client objectives / analytical plan into clear
deliverables with associated priorities and constraints
Organize/Prepare/Manage data and conduct quality checks to ensure that the analysis dataset
is ready
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.
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
Interpret the output in context of the client’s business and industry to identify trends and
actionable insights
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
Be able to take client calls relatively independently, and interact with onsite leads (if
applicable) on a daily basis
Discuss queries/certain sections of deliverable report over client calls or video conferences
Client Management
Act as client lead and maintain client relationship; make independent key decisions related to
client management
Be a part of deliverable discussions with clients over telephonic calls, and guide the project
team on the next steps and way forward
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