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Senior Manager – Data Analytics

Roles and responsibilities

Specifically, Senior 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

Most Important Requirements:

  • Superior problem solving abilities and strong analytical thinking
  • Desire to work in a fast paced, challenging environment where you need to push yourself all the time
  • Excellent communication skills, both written and verbal
  • Solution orientation and self-drive

Ideal Candidate

  • 8-10 years of relevant advanced analytics experience in Marketing, CRM, Pricing in either Retail, or CPG industries. Other B2C domains can be considered
  • 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
  • Experience in handling client calls and working independently with clients
  • Understanding of consumer businesses such as Retail, CPG or Telecom
  • 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
  • Knowledge of advanced statistical techniques like Decision trees, different types of regressions, clustering, Forecasting (ARIMA/X), ML, etc.

 Other Skills

  • Excellent communication skills (both written and oral)
  • Ability to create client ready deliverables in Excel and PowerPoint
  • Optimization techniques (linear, non-linear), and knowledge of supply chain
  • VBA, Excel Macro programming, Tableau, Qlikview

Education 

  • Engineers from top tier institutes (IITs, DCE/NSIT, NITs) or Post Graduates in Maths/Statistics/OR from top Tier Colleges/Universities
  • MBA from top tier B-schools