Data Analysis: Analyze large datasets to uncover patterns, trends, and insights, using statistical and machine learning techniques
Model Development: Develop and implement predictive models, recommendation systems, and algorithms to solve complex problems, such as user engagement, content personalization, or ad targeting
A/B Testing: Design and conduct A/B tests to evaluate the impact of product changes and feature enhancements, helping to inform product development and optimization
Data Visualization: Create compelling data visualizations and dashboards to communicate findings and insights to cross-functional teams
Data Engineering: Collaborate with data engineers to access, clean, and preprocess data for analysis
Ensure data pipelines are efficient and reliable
Machine Learning: Utilize machine learning frameworks and tools to build and deploy models for various applications, such as image recognition or natural language processing
Natural Language Processing (NLP): Apply NLP techniques to analyze and extract insights from unstructured text data, such as user comments or posts
Deep Learning: Work on deep learning projects, including neural network architectures, to solve complex problems, like image and video analysis