The Smart Cube - Assistant Manager - Data Analytics

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 the 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 the 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 :

- 4-7 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