Swayonok Kundu

I am a statistician ,running end to end Machine learning in Python and R .Vizualisation in tableau.

A post graduate in Statistics, having found my passion in data science, I truly believe "the goal is to turn data into information and information into insight" ~ Carly Fiorina. I enjoy my profession and would like to carve a niche for myself in the analytics industry.

A keen observer ,detail oriented with strong communication and interpersonal skills.

Trained in Statistics, analytics ,data mining, predictive modeling and analysis with complex datasets for problems in risk analysis , demand forecasting. and business decision making .
Use R and SAS to create meaningful and actionable analysis using transaction, contextual and market research data, enabling clients to develop customer focused strategies.

Working as Business Analyst in Accenture Digital.
Trusted data and actionable insights.
Specialties :Technical competency in the area of statistical techniques like Decision tree,Modelling in Regression, Time series , Classification techniques , Data Mining application ,Text mining,Machine learning for forecasting and regression

Experience on data analysis with statistical techniques in R,Python,SAS 9

Software competency: Exposure with statistical software like R , SAS 9.2,SPSS MODELER 16.0, MS Excel,Tableau and Alteryx.

•Working as a Senior Analyst in Supply chain Analytics with Accenture having more than 4 years of experience into Predictive Modelling , Supply Chain Management
•Hands-on Experience in SAS,R ,SQL,Python,Tableau and Alteryx in Windows environment.
•Statistical modelling algorithms like Linear ,Logistic Regression, Decision Tree , clustering techniques and Forecasting.

Working in forecasting and optimisation problem for Workforce in an American multinational diversified hospitality company.
Incorporating online retail sites reviews to generate sentiment score and use that as one of the causal variable for future sales prediction in UCM model.

Digital analytics for any website coverage and getting insights through google analytics.certified data mining in R through linkedin learning.

Building capacity planning models for Operations working on Defined Benefits and Defined Contributions.Forecasting the incoming volume for different business process .
Incoming Volume prediction for different operations based on the chatbot queries by NLP ultimately routing the volumes to the optimized team that would save Operations head count efforts.