Senior Data Analyst

Role and Responsibilities

The Senior Analyst plays an important role in delivering analytical projects successfully and aiding strategic decision making for Fortune 500 / FTSE 100 companies and other services organizations, with main focus on the Supply Chain function.

They are expected to quickly become independent on their analysis and bring innovation and creativeness in the analytical solutions. Specifically, senior analysts need to be able to –

• Work on multiple projects of varying complexities, ensuring top notch quality and timeline adherence
• Understand the client objectives and work with the Project Lead 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 and manage data and conduct quality checks to ensure that the analysis dataset is ready
• Conduct sanity checks of the analysis output based on reasoning and common sense, and be able to do a rigorous self-review, 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
• Visualize and present the findings through a PPT or a Business Intelligence dashboard (Tableau, Qlikview, etc.); highlight the key takeaways from a business perspective
• Take client calls relatively independent and interact with onsite leads (if applicable) on a daily basis; discuss queries/certain sections of deliverable report over client calls or video conferences
• Explore and implement simple statistical and analytical techniques like linear/non-linear regression, segmentation, time series forecasting, etc. 

Requirements

 The ideal candidate needs to have –

• Bachelor degree, preferably in Mathematics, Informatics or Economics
• Proficiency in English (both written and verbal)
• Experience in interacting with clients and working independently
• Prior experience in analytics across a variety of projects starting from basic reporting, dashboard development, EDA, segmentation, forecasting, predictive modeling, optimization
• Hands-on knowledge in using MS Office Suite: Access/ SQL, VBA, Excel, PPT
• Working knowledge across multiple data types and files like flat files and RDBMS files
• Working knowledge in one or more data science programming languages such as R or Python
• Experience in using data visualization tools such as Tableau, Qlikview or Power BI
• 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
• Solution orientation and self-drive 

Desirable Skills
Other nice-to-have skills that represent an advantage include –

• Working knowledge in database management tools/platforms such as SQL Server, Teradata, Hadoop, Spark; on premise or on the cloud
• Experience in machine learning, NLP, and knowledge about Hadoop, MapReduce
• Knowledge of advanced statistical techniques like decision trees, different types of regressions, clustering, forecasting, etc.; machine learning algorithms like Random Forest, SVM, ANN, etc.