Senior Analyst - Marketing Analytics - Retail/CPG/Life Sciences/Industrial Domain

Job Description - Senior Analyst

Roles and responsibilities :

A senior analyst plays a very critical role in delivering analytical projects successfully and aiding strategic decision making for Fortune 500 / FTSE 100 companies, and other services organizations across retail, CPG, Life Sciences, and Industrial domain. They are expected to work independently on their analysis, and try and bring the innovation and creativeness in their analytical solutions. Specifically, senior analysts 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

Ideal Candidate :

- 2-4 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