Namita Pradhan

adh1t4@r.postjobfree.com mailto:adh1t4@r.postjobfree.com +1-951-***-****

LinkedIn: https://www.linkedin.com/in/namita-pradhan-244431149 GitHub: https://github.com/namitapradhan26

EDUCATION

University of California - Riverside December 2019

Master of Science in Electrical Engineering Specialization: Signal Processing and Machine Intelligence

Veermata Jijabai Technological Institute, Mumbai, India May 2018

Bachelor of Technology in Electronics Engineering

EXPERIENCE

Jr. Data Scientist – Pegasus Knowledge Solutions Inc. July 2020 – Present

Built a pilot model for talent analytics using skill match score use case by matching skills extracted from resumes to those in job descriptions by using NLP techniques

Engaged in enhancing Product Data Dictionary and closely worked with the Data Scientist learning SAS and SPSS tools

Worked on building a talent analytics model to predict the propensity of a candidate accepting an offer given to them using Logistic Regression

Performed R&D for finding analytical solutions of several business problems from clients

Lead a team of interns to put together a banking analytics dashboard running in a static way and created a BRD for it

Data Science Analyst – Ace Ebiz Consultants Pvt. Ltd. May 2017 – August 2018

Gathered and merged big data from 2 ETL systems using SQL, which in turn were sourcing transaction data from 30 primary sales locations and 5 manufacturing/distribution locations of a pharmaceutical company spread across India

Predicted future business by designing and building Random Forest and Boosting regression algorithms and provided recommendations to the management teams about peak sales and inventory target which showed a recall of about 91%

Assisted with dashboard development using Tableau to visualize sales and inventory in different parts of the country

Researched new ETL technologies and tools and applied them to enhance the overall performance of the model

Bachelor Thesis – Veermata Jijabai Technological Institute August 2017 – May 2018

Visualized and analyzed 5 years’ Bombay Stock Exchange data using Tableau, and did feature engineering like scaling and imputation using Python

Proposed a novel indicator called Open Close Crossover Indicator which provided a good accuracy as compared to the other KPIs in stock market analysis theory

Estimated stock pricing trends using KNN to achieve an overall accuracy of 82%

Authored a paper, along with my team, on this model which was accepted and published by Asian Society for Academic Research

ACADEMIC PROJECTS

Continual Learning using Dynamically Expandable Network June 2019 – September 2019

Employed virtual GPUs using Kubernetes cluster for implementing continual deep learning using CNN on MNIST data set for object recognition

Compared our algorithm with regular feed-forward network using Python and observed over 10% increase in accuracy

Studied and implemented new data set called CORe50 using transfer learning from pre-trained model to encounter a benchmark performance for continual learning

Data Compression using GPU parallel processing January 2019 – March 2019

Pre-processed data before feeding it to the LZ77 algorithm where each thread block with different starting point is compressed independently

Generated the Huffman tree serially on the CPU using C language, computed the prefix sum and generated encoded byte, later compressing the bit stream parallelly on GPU CUDA kernel

Achieved a compressed file that had smaller size as compared to the original file

TECHNICAL SKILLS

Programming Languages: Python, MATLAB, SQL, Cuda C, R, C, C++

Math skills: Stochastic processes, Linear algebra, Statistics, Time Series, Queuing theory

Libraries/Software skills: TensorFlow, PyTorch, Keras, Scikit-learn, Data structures, ETL Pipeline, Data Visualization, Image Processing Pipeline, SparkML pipeline, SMOTE, Recommendation system, SAS scripting using SWAT, t-SNE for Dimensionality Reduction, Word2Vec for Natural Language Processing, PostgreSQL, AWS EC2, GluonCV, Apache MXNet

Programming, Development and Simulation Platform: Anaconda, MATLAB, OpenCV, SQLite Studio, Tableau, GitHub, Kubernetes, AWS, Docker, IBM Watson Studio, Microsoft Excel, RStudio, Jira, Real-Time Embedded System

Guided project: Image Classification with Amazon SageMaker – Coursera

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