Company 

Location

Job type

Job Description

Roles and Responsibilities

• Perform NLP (Natural Language Processing) computations on small and large corpora
• Scrape and parse relevant text for classification
• Work with our Quality Assurance Lead to test entity extraction and related content algorithms to further refine our system to be more accurate
• Work with our Data Science Lead to create additional frameworks and features to improve the accuracy of our existing algorithm
• Assist with building and validating mathematical models applied in the field of Natural Language Understanding.
• Assist in the formulation and construction of an automated process to determine individual story significance within a chain of linked articles or more succinctly to understand a developing story's trajectory. Ultimately, the project aims to take a time series of events that are interconnected in a non-trivial/non-coincidental way, and by using thematic and contextual information from a large number of media report about the series of events we aim to reconstruct the original series of landmark events leading to the current state of that particular event. Later we will attempt to give a broad/high level understanding as to the trajectory in the series of events and their future.
• Create sample sets to further train our machine learning algorithms
• Opportunity to work with the CEO on marketing campaigns and business development initiatives

Minimum requirements

• Bachelor's degree
• Relative ease with mathematics, Python and machine learning
• Positive interaction with the team and management
• Colab or PyCharm
• Pandas or SQL
• Desire to learn more about startups

Desired

• Atlassian Jira, Bitbucket, Confluence
• Git
• Image processing skills
• Strong matrix and linear algebra
• Strong statistics, probabilities, distributions

Job Settings 

Application Settings

• Book here an interview with us
• Send here on Hanshake a motivation letter/message where you discuss the fitness of your profile to this internship and company
• After 15 minutes chat we will inform you about next steps
• We ask technical and mathematical questions at the interview
• Make sure you can easily summarize NN, NLP, CNN, SVM, Logistic regression, Kmeans, KNN etc. And know the difference between normal and power (Pareto, Zypf) law distributions.
• Arrange for 2-3 recommendations, to be sent if interview output is positive

Language