Data Scientist

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August 28

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Sensor Tower

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SaaS • Marketing • Gaming

Sensor Tower is a company that provides comprehensive data solutions to grow and optimize mobile strategies. It offers various intelligence products like Ad Intelligence, App Intelligence, Consumer Intelligence, and Store Intelligence for in-depth insights into mobile user behavior and digital advertising trends. The company's platform is leveraged by marketers to gain visibility into the digital advertising ecosystem across different regions including North America, EMEA, and APAC. Sensor Tower helps businesses make informed decisions and refine strategies through sophisticated analytics, enabling them to stay ahead in the competitive market. Trusted by global digital leaders, Sensor Tower is recognized for its robust data-driven insights for mobile apps, games, and digital advertising strategies.

201 - 500 employees

Founded 2013

☁️ SaaS

🎮 Gaming

💰 $45M Private Equity Round on 2020-05

📋 Description

• Data Scientists at Sensor Tower are hybrid Data Scientists and Software Engineers. You would take data all the way from doing initial analysis to building data pipelines to final model implementation and monitoring. Data Scientists take full ownership of the back-end of the products they’re working on. We are looking for a hands-on thinker to help harvest new insights from our constantly growing foundation of quantitative information collected from the mobile app ecosystem.

🎯 Requirements

• Master’s degree or above in mathematics, statistics, or computer science. • 3+ years applied experience in business intelligence, data mining, analytics, or statistical modeling in technology or mobile industries OR 2+ years applied experience in data science in mobile market intelligence. • Ability to write code that is ready for production (Python and Ruby preferred). • Experience with adjusting data for bias. • Substantial experience with databases, querying data, and data structure manipulation. • Ability to communicate effectively with technical developers and non-technical marketing business partners. • Ability to produce rough timelines for deliveries plus solid understanding of steps necessary to complete a project. • Ability to come up with a rough project structure from scratch. • Ability to critically analyse given data, ask probing questions, and perform own research. • Substantial knowledge of statistical modeling techniques. • Mastery of one or more statistical visualization or graphing toolkits such as Excel, Jupyter Notebooks, or Google Spreadsheets.