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

• Prototype machine learning models in Python or Ruby. • Analyze query performance to ensure calculation efficiency. • Write tests for the implementation of machine learning models. • Collaborate with back-end engineers to understand the raw data being collected. • Collaborate with front-end engineers to create data visualizations for both external and internal customers. • Conduct ad-hoc data analysis based on requests from the Sales, CSM or Contents team. • Present results of various data analysis.

🎯 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.