Porush Goyal

Data Engineer

New Delhi, Delhi, India3 yrs 7 mos experience
Highly Stable

Key Highlights

  • Experienced in data engineering and machine learning.
  • Proficient in Python and SQL for data analysis.
  • Strong background in web development and GUI design.
Stackforce AI infers this person is a Data Engineer with expertise in machine learning and web development.

Contact

Skills

Core Skills

Python (programming Language)Machine LearningData AnalysisWeb DevelopmentDatabase Management

Other Skills

Analytical SkillsApache AirflowApache SparkData EngineeringData PreprocessingGUI DevelopmentInterpersonal SkillsMachine Learning AlgorithmsMicrosoft AzureMySQLProblem SolvingPrototype DesignSQLTK SolverTableau

Experience

To the new

3 roles

Senior Data Engineer

Promoted

Oct 2024Apr 2025 · 6 mos

Data Engineer

Promoted

Aug 2021Sep 2024 · 3 yrs 1 mo

Data Engineer

Feb 2021Jul 2021 · 5 mos

Universal technical systems

Summer Internship

May 2020Jul 2020 · 2 mos · Pune, Maharashtra, India

  • During this internship I worked on a project where our team had to merger the functionality of TK Solver ( Company's own software ) with machine learning prospects of Python programming language. We created a machine learning model for the crop production after which further mathematical calculations were carried in TK Solver model. To provide it a simplified look for user interaction a GUI was created using the Tkinter package. I was responsible for the GUI and back-end linking between TK Solver to Python and Python to Tkinter (GUI)
Python (Programming Language)Machine LearningGUI DevelopmentTK Solver

Ducat education

Data Science

Sep 2019Nov 2019 · 2 mos · Gurugram, Haryana, India

  • Titanic dataset has been chosen for the analysis. In this analysis the dataset has been analysed to predict the port of embarkation by generating a prediction model using all the relevant attributes in the dataset. To generate a model, data needed to be pre-processed to remove the columns that are not required, standardise all the features, filling the NAN values with the average value of the column. Mapping the categorical data to numeric value to improve the prediction accuracy of the model. After the pre-processing is done the data was split into two groups training data and testing data. Training data is used for the creation of the model while the testing data is used to check the validity of the model. Two algorithms namely Decision Tree, K-Nearest Neighbour and Random Forest were applied, and the accuracies of the models generated from these algorithms was compared with each other in order to select the most suitable one for the analysis of the dataset.
Data AnalysisData PreprocessingMachine Learning AlgorithmsMachine Learning

Hate2wait

Summer Intership

Jun 2019Aug 2019 · 2 mos · Gurugram, Haryana, India

  • During my internship I did a project on web development in which I created prototype website. The website contained the functionality allowing the user with the role of a teacher to create their own MCQ tests. They would have access to all their created test. They can edit, view, delete them whenever they want to. Project also included another role that goes by the name 'student'. The user who has the role of a student will be able to attempt any of the tests created so far by all of the teachers. Further it uses MySql to store the data
Web DevelopmentMySQLPrototype DesignDatabase Management

Education

The NorthCap University

Bachelor's degree — Computer Science

Jan 2017Jan 2021

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