Hello! My name is Arun Ramachandran and I had worked at Wipro Technologies as a Java Developer and at World Wide Fund for Nature in India as a Research Analyst.
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i2e Consulting | Wipro Technologies / Wipro Digital | World Wide Fund for Nature in India | Chegg - India
Software Engineer
June 15, 2026 – Present
Applied-Data-Science-Capstone-Segmenting-and-Clustering-Neighborhoods-in-New-York-City
March 12, 2021 – March 12, 2021
In this lab, you will learn how to convert addresses into their equivalent latitude and longitude values. Also, you will use the Foursquare API to explore neighbourhoods in New York City. You will use the explore function to get the most common venue categories in each neighbourhood, and then use this feature to group the neighbourhoods into clusters. You will use the k-means clustering algorithm to complete this task. Finally, you will use the Folium library to visualise the neighbourhoods in New York City and their emerging clusters.
View ProjectApplied-Data-Science-Capstone-Foursquare-API
March 6, 2021 – March 6, 2021
In this lab, you will learn in details how to make calls to the Foursquare API for different purposes. You will learn how to construct a URL to send a request to the API to search for a specific type of venues, to explore a particular venue, to explore a Foursquare user, to explore a geographical location, and to get trending venues around a location. Also, you will learn how to use the visualization library, Folium, to visualize the results.
View ProjectCoursera_Capstone
March 5, 2021 – March 5, 2021
Peer-graded Assignment - Capstone Project Notebook This capstone project course will give you a taste of what data scientists go through in real life when working with data.
View ProjectPython-Project-for-Data-Science-Analyzing-Historical-Stock-Revenue-Data-and-Building-a-Dashboard
March 5, 2021 – March 5, 2021
As a data scientist working for an investment firm, you will extract the revenue data for Tesla and GameStop and build a dashboard to compare the price of the stock vs the revenue.
View ProjectExtracting-Stock-Data-Using-a-Python-Library
March 4, 2021 – March 4, 2021
In this lab, you will use a Python library to obtain financial data. You will extract historical stock data using yfinance.
View ProjectMachine-Learning-with-Python-Peer-graded-Assignment-The-best-classifier
March 2, 2021 – March 4, 2021
In this project, you will complete a notebook where you will build a classifier to predict whether a loan case will be paid off or not. You load a historical dataset from previous loan applications, clean the data, and apply different classification algorithm on the data. You are expected to use the following algorithms to build your models: k-Nearest Neighbour, Decision Tree, Support Vector Machine, Logistic Regression. The results is reported as the accuracy of each classifier, using the following metrics when these are applicable: Jaccard index, F1-score, Log Loss.
View ProjectMachine-Learning-with-Python-Collaborative-Filtering-on-Movies
March 1, 2021 – March 1, 2021
Recommendation systems are a collection of algorithms used to recommend items to users based on information taken from the user. These systems have become ubiquitous can be commonly seen in online stores, movies databases and job finders. In this notebook, we will explore recommendation systems based on Collaborative Filtering and implement simple version of one using Python and the Pandas library.
View ProjectMachine-Learning-with-Python-DBSCAN-Clustering
February 26, 2021 – February 26, 2021
Density-based Clustering locates regions of high density that are separated from one another by regions of low density. Density, in this context, is defined as the number of points within a specified radius. In this section, the main focus will be manipulating the data and properties of DBSCAN and observing the resulting clustering.
View ProjectData-Analysis-with-Python-House-Sales-in-King-County-USA
January 27, 2021 – January 27, 2021
In this assignment, you are a Data Analyst working at a Real Estate Investment Trust. The Trust will like to start investing in Residential real estate. You are tasked with determining the market price of a house given a set of features. You will analyze and predict housing prices using attributes or features such as square footage, number of bedrooms, number of floors, and so on. This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015.
View ProjectBoston-Housing-Data-Statistical-Analysis-using-Python
January 17, 2021 – January 19, 2021
The code sample is from the Boston Housing Data Analysis which was performed using Python. The code basically involved various data visualizations on the columns and thereby extracting meaningful information from the graphs like Scatter Plots, Boxplots. Then we used those graphs for analysis via hypothesis testing like code sample included t-test, ANOVA, Correlation and other metrics to extract information which supports the visualizations we prepared. It also contains Linear Regression to create a machine learning model to support our analysis. The code sample included Pearson test for continuous variables and Chi-Square Test for the categorical variables.
View ProjectCultural Fit Analysis
The candidate's projects are primarily focused on data science and machine learning, indicating a strong interest in these areas. The projects are diverse within the data science domain, covering housing price prediction, statistical analysis, geographical clustering, and recommendation systems. The target role is 'Software Engineer', which may require a broader set of software development skills beyond data science. The current experience lists 'Software Engineer' at multiple companies, but no specific skills or project details are provided for these roles, making it difficult to assess alignment with a general software engineering role. The candidate's experience level is listed as 0, which contradicts the listed professional experience, suggesting a potential data entry error or a very recent start to professional work.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems and apply learned concepts. However, without psychometric test results or interview data, it is not possible to assess soft skills like logical reasoning, work attitude, stress handling, or team collaboration.