I like to solve problems. Being in the field of Data Science has given me a chance to leverage my analytical and technical skills to do that. I've had experience in deploying end-to-end analytical solutions, while working collaboratively to deliver the results in production environment with deadlines. End-to-End analytical experience includes • Defining business problem: Understand the business objective and define success criteria. Understand the current processes and the scope of the problem being solved. • Chart the analytical approach: Use Hypothesis Testing and EDA to understand/prepare the data and define the approach (R, Python, Excel) • Proof of Concept: Work with the end user to iteratively develop a working solution that meets all the objectives and constraints (business, environment, tools, data, timeline) that can be scaled (Python usually done in MarkDowns and Jupyter Notebooks) • Implementation in production: Scale the above solution with right infrastructure/tools to meet the complete scope • Evangelize the results: Develop the right KPIs to monitor the performance of the solution and communicate the results to the end user. Facilitate changes to the solution to aid the consumption of the product. Empower the end user with the required information to use the product. (Tableau, PPT) • Automate the process: Remove human touch points wherever possible. Set up alerts to easily monitor the process. Skills Summary- • Modelling and Statistical Analysis- Regression,Classification,Neural Networks,Clustering, Time Series Modeling, A/B Testing • Analysis Tools/Languages-Python( Natural Language Toolkit,NumPy, Pandas, scikit-learn, auto-sklearn,),StanfordNLP,Tensorflow,Hadoop,Apache Spark,YARN, R(dplyr, ggplot2, RSQLite),MySQL, Tableau