Flipkart - Associate - Business Analytics - CS Analytics

Location - Bangalore

About Flipkart:

In 2007, we started the Flipkart journey by selling books online. But now, over a decade later, our story is quite different. Today, Flipkart is India's largest online marketplace and one of India's leading technology powerhouse that is disrupting the way India shops online. What has got us here? The dynamic, passionate and talented folks we call Flipsters!

Our core values define our identity and form the basis of our actions and reflect in everything that we do at Flipkart. Values enable us to shape the desired organizational culture in which each Flipster can thrive and be at their best.

We believe in taking bold bets and changing the paradigm, having a sense of urgency to solve problems strategically and putting great ideas into action. We look at the world from our customer's point of view and keep customers at the heart of everything we do. We strive to do the right thing always and be committed to our customers and stakeholders.

About the Team : 

Contact Centers within e-Commerce industry across regions in India are in emerging phase and is dynamic. With the growing scope of activities and multiplicity of business and departments involved there is a need to transfer best practices that improve productivity, service efficiency, performance management and analytics through business intelligence in C-Ops vertical of Flipkart. With the intent of ensuring that with standardized best in class Contact Centre Performance Management and Analytics and Business Intelligence, a team member with the relevant experience and expertise is required.

What you'll do:

- You will work closely with internal Flipkart Teams to identify, define, collect, and track key business metrics for products or business processes.

- Pull data required to conduct business analysis, build reports, dashboards and metrics to monitor the performance.

- Work with the stakeholders to take data driven decisions.

- Troubleshooting and debugging of various BI tools to support various Contact Centre performance management and analytics and other Business needs

- Database Management of different sources and customer tagging databases to create integrated views that can be used to drive decision making

- Working with several medium large and complex SQL databases and SQL queries for data mining.

Use advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities for various teams in CX

Own the exploratory data analysis of metrics and assist the CX stakeholders in building analytical views in PowerBi, provide RCAs, prepare storyboards, perform statistical validations for various hypotheses, mine text data etc.

Own the design and development of projects that involve predictive analytics and assist the CX stakeholders in delivering the driver models for the metrics, improvement in forecasting models, application of machine learning algorithms for solving business problems.

What you'll need:

- Degree in IT or related major preferred

- 2+ years Data Mining experience

- Strong knowledge of SQL, Power Bi, MS Excel, Programming in R & Python

- Must be a self-starter who requires minimal supervision, with excellent problem-solving skills

- Prior experience in the BI & Analytics function of a large scale B2C domestic/international contact centre or consulting firm . (Mandatory)

Advanced Excel Skills (Mandatory) : 

- Strong statistical & machine learning programming skills using R and Python (Mandatory)

- Expert level data manipulation skills using libraries like dplyr(R), pandas(python) (Mandatory)

- Strong SQL skills, ability to perform effective querying involving multiple tables and subqueries (Mandatory)

- Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units (Mandatory)

- Good understanding and practical application of Machine Learning concepts like Regression (Linear, Logistic, Regularization), Classification using Supervised as well as Unsupervised Learning (K-Means, KNN, SVM, Decision Trees, Random Forests, Naive Bayes) (Mandatory)

- Exposure to Natural Language Processing techniques for Sentiment Analysis, Text Classification, Comment Analysis (Preferred)

- Exposure to Time Series Modelling techniques like ARIMA, ARIMAX, Prophet (Preferred)

- Experience working with and creating databases and dashboards using all relevant data to inform decisions (Preferred)