
Data Science Practitioner
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Assessing your cultural and operational fit
Insofe
Data Scientist
June 16, 2026 – Present
Predicting-Genres-From-Movies-Data
April 6, 2020 – April 6, 2020
Use the movies metadata file to predict the genres field.
View ProjectRossmann-Store-Sales
March 5, 2020 – March 5, 2020
Forecast sales using store, promotion, and competitor data
View ProjectTwitter-Sentiment-Analysis
December 12, 2019 – December 12, 2019
The objective of this task is to detect hate speech in tweets. For the sake of simplicity, we say a tweet contains hate speech if it has a racist or sexist sentiment associated with it. So, the task is to classify racist or sexist tweets from other tweets. Formally, given a training sample of tweets and labels, where label '1' denotes the tweet is racist/sexist and label '0' denotes the tweet is not racist/sexist, your objective is to predict the labels on the test data set.
View ProjectHuman-Activity-Recognition-using-sensor-data-through-Deep-learning-Techniques
November 12, 2019 – November 22, 2019
Human activity recognition (HAR) is gaining importance due to wearables and sensors data associated with it. Different from traditional Pattern Recognition methods, deep learning can largely relieve the effort on designing features and can learn much more high-level and meaningful features by training an end-to-end neural network. You need to find the dataset from open resources which can provide you human activity data.
View ProjectRobust-Model-For-Class-Imbalance
November 12, 2019 – November 12, 2019
There is no particular definition for imbalanced class of data. In general, data that is not balanced is called imbalanced. However, there are infinite possibility of imbalanced class of data. Usually, we do up-sampling or down-sampling of the imbalanced data and make it balanced before applying machine learning models. In both the cases, we lose information about that data set. In this project, we would like to investigate what are the best models through all possible imbalanced situation of a data set.
View ProjectCultural Fit Analysis
The candidate's personal projects show initiative and a self-driven approach to learning and applying data science concepts. The diversity of project topics (NLP, time series, classification, deep learning) suggests a broad interest within the data science domain. However, the lack of team-based projects or contributions to open-source initiatives limits the assessment of collaborative cultural fit. The current role as a Data Scientist aligns well with the target role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.