Help serve Googles worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. Youll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
responsibilities :
Design and analyze experiments, including randomized controlled trials, to measure and guide the impact of Ads Planning initiatives.
Define key performance indicators and their associated value for advertisers and Google across various Ads Planning initiatives.
Formulate metrics that capture the impact of Ads Planning tools on advertiser spend, reach, Google business growth, and agreement value.
Develop methodologies for conducting impact studies for agencies and third-party tools.
Collaborate with cross-functional teams to ensure the accuracy and feasibility of measurement strategies.
requirements-expected :
Bachelors degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field or equivalent practical experience.
8 years of experience in using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years experience with a Masters degree.
Experience with methods of statistical data analysis (e.g., linear models, hypothesis testing, multi-level models, Bayesian methods, etc.).
Experience with A/B testing or other experimental design methodologies.
benefits :
sharing the costs of sports activities
private medical care
sharing the costs of foreign language classes
sharing the costs of professional training & courses
life insurance
remote work opportunities
fruits
corporate products and services at discounted prices
