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Wynd Labs
Data Scientist
about 2 months ago | 309 views | 6 applications

Data Scientist


About the company

Wynd Network enables access to public web data through decentralized data scraping tools such as our first product, Grass. Grass is a network sharing application that allows users to sell their unused bandwidth. Effectively, this is a residential proxy network that directly compensates individual residential IPs for the bandwidth they provide. Wynd will route traffic equitably among its network and meter the amount of data that each node provides to fairly distribute revenue. In non-technical terms: we're unlocking everyone's ability to earn from a passive income stream by simply selling the unused internet bandwidth on personal devices (laptops, smartphones).

Job Summary

Your day-to-day:

📍Analyzing and interpreting complex time series data to provide actionable insights and solutions. 📍Designing, implementing, and maintaining data-driven models and algorithms. 📍Collaborating with cross-functional teams to understand data needs and deliver timely solutions. 📍Ensuring data quality and integrity throughout all processes. 📍Utilizing Optical Character Recognition (OCR) technology to convert different types of documents into editable and searchable data. 📍Continuously researching and implementing best practices in data science and machine learning. 📍Contributing to the development and improvement of internal data processing tools and infrastructure.

What experience you need:

📍Bachelor’s, Master’s, or Doctoral degree in Data Science, Computer Science, Statistics, or a related field. 📍A minimum of 3 years of work or research experience dealing with large datasets. 📍Strong coding skills in Python or other object-oriented programming languages. 📍Graduate-level knowledge of statistics, including but not limited to hypothesis testing, regression analysis, and probability. 📍Excellent work ethic and the ability to thrive in a fast-paced startup environment. 📍Strong problem-solving skills and attention to detail. 📍Good communication skills, with the ability to articulate complex data concepts to non-technical stakeholders. 📍Experience working in a high output team.

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