Prakhar Srivastava

Software Engineer

Bengaluru, Karnataka, India7 yrs 5 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Integrated post-graduation in Information Technology from IIIT Gwalior.
Experience in Machine Learning and Natural Language Processing.
Proficient in Python and data analysis techniques.

Stackforce AI infers this person is a Data Science professional with a focus on Machine Learning and Natural Language Processing.

Contact

prakhar.srivastava@harman.com LinkedIn

Skills

Core Skills

Machine LearningNatural Language Processing (nlp)Data AnalysisPredictive Modeling

Other Skills

AlgorithmsCC (Programming Language)C++Computer NetworkingData StructuresDatabase Management System (DBMS)Object-Oriented Programming (OOP)Operating SystemsPythonSQL

About

I pursued integrated post-graduation in Information Technology from IIIT Gwalior. My interest areas include data structures and algorithms, DBMS, Natural Language Processing and Machine Learning.

Experience

Harman international

2 roles

Engineer 1

Promoted

Feb 2023 – Present · 3 yrs 1 mo

Associate Engineer, SW

Oct 2020 – Feb 2023 · 2 yrs 4 mos

Core compete, part of accenture

Data Science Intern

May 2019 – Jul 2019 · 2 mos · Hyderabad, Telangana, India

Build automated Python modules for time series forecasting and used Fossil's data for evaluation of the developed model.
After providing dataset with generic column names, attribute names which are to be made SKU, TimeId parameter according to which generated time series will be indexed and the sales quantity parameter which is to be forecasted, the best model with the optimized model parameters is selected and forecast is generated for the specified number of months.

PythonMachine learningNatural Language Processing (NLP)

Exam preparation online

Intern

Aug 2018 – Oct 2018 · 2 mos · Work From Home

Performed data analysis and predictive modeling to extract meaningful business insights. My role was mainly related to data cleaning, exploring different models and applying them.

Data analysisPredictive modeling