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Project Trainee Resume


  • In - depth knowledge of Data Analytics with an emphasis on ML, AI, NLP, Statistical Analysis.
  • Motivated and passionate to learn new technical and personal skills.
  • Good Collaborated with excellent interpersonal communication, orchestrated, mentoring and multi-tasking, follow-up & presentation skills, a strong rapport with associates at all levels & disciplines, excellent team member with the ability to lead projects.
  • Considered as a well-organized employee with “can-do” attitude.


Analysis Tools: MS Excel, R Studio, Tableau, SQL Server

Programming: Python, R, SQL, SAS, Big Data (Hive, Map Reduce, Pig, Impala, HDFS, AWS)

Analysis Techniques: Text Mining, Supervised and Unsupervised algorithms (Linear, Logistic, SVM, Decision Tree, Random Forest, K-means, KNN, PCA, NLP), classification, regression, NumPy, Pandas, TensorFlow, Keras, Scikit-Learn, Matplotlib



Project Trainee


  • World’s largest cooperative in fertilizer sector; Confidential has retained its number 1 position in Fertilizer & Argo Chemical sectors. Project is based on to find the working capital situation of the company.
  • Performed Cost Analysis to helping in improve working capital Pay creditors to ensure continued supplies of goods and services.
  • Performed some interesting predictive analysis by using time-series analysis of products raw material demand.
  • Trained a team of four employees on application functionality of 150 applications, technical know-how and resolution techniques in production support projects, refining the resolution rates of the team by 60%.


Training Project Coordinator


  • Supported to the Product Development Team in project work by developing new beverage products.
  • Assisted in batching, analytical testing, flavor screening, QC / QA equipment calibration, keeping lab materials stocked, and helping maintain a clean and orderly laboratory.
  • Learned formulation and process basics across a wide variety of beverage matrices including juices & protein drinks.
  • Analyzed customer data to solve frequent occurring issues and incidents reported in Citrix. Proposed solutions helped to improve customer satisfaction rate by 20%.


Predictive Analysis


  • Identified the future demand patterns of wind energy in Texas within next 5 years by using Regression Models and ARIMA forecast model from the past ERCOT 10 years of total energy consumption data and 3 years of wind hourly load data.

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