Description:

The Senior Data Scientist at Sensor Tower will leverage digital advertising along with mobile, desktop, and OTT industry knowledge to drive strategies that improve the accuracy and offerings for our Digital Marketing insights solution.
This solution draws upon large-scale data (over 140 billion data records) and allows customers to uncover insights like which apps or brands are advertising the most by channel and platform, which creatives are performing the best across certain ad networks, which ad network an advertiser is marketing on the most, and how much advertisers are spending in a channel and country.
Responsibilities include executing the development of data modeling algorithms, focusing on analyzing large sets of data, building models, and ensuring data accuracy, reliability, and consistency.
The role involves developing, refining, and bringing data models to production, working on models consumed by end users, building internal tools, and generating one-time reports.
The Senior Data Scientist will consult on the use of AI to improve workflows for data extraction and classification.
The position embraces a quick build, measure, and iterate cycle to bring products to market and involves collaboration with world-class engineers and data scientists.
The individual will act as a subject matter expert for digital advertising.

Requirements:

A degree in Mathematics, Statistics, Computer Science, or a related engineering, technical, or quantitative field is required.
A minimum of 4 years of experience as a Data Scientist in ad-tech, mar-tech, or data analytics companies is necessary.
Experience in business intelligence, data mining, analytics, and statistical modeling disciplines is required.
The candidate must have skills in analyzing and presenting data insights and code, and effectively communicating with both technical developers and non-technical marketing business partners, teammates, and leadership.
Proficiency in implementing machine learning algorithms and working end-to-end on machine learning pipelines in production is essential.
Experience in data engineering, including working on ETL pipelines, crawling APIs and websites, and automating outputs is required.
The candidate should be capable of setting and meeting detailed timelines and expectations while executing projects and developing them in a resilient manner.
Skills in data research, particularly in identifying necessary edge cases for comprehensive data understanding, are important.
Proficiency in programming with Python or Ruby, and familiarity with AWS S3, MongoDB, PostgreSQL, AWS Redshift, or similar database technologies is required.
Experience using Jupyter notebooks and one or more statistical visualization or graphing toolkits such as Excel, Qlik Sense, or Tableau is necessary.

The position offers a flexible work environment that allows employees to connect with the people, places, and activities they love.
Employees benefit from flexible time off, enabling them to shape their time away from work.
A health and wellness stipend is provided to help employees achieve and maintain a healthy lifestyle through physical and mental fitness.
A monthly internet stipend and a one-time $500 home office stipend are included to support remote work needs.