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Senior Business Data Scientist, Marketing

Fresher   All India, Gurugram   02 Jun, 2026
Job LocationAll India, Gurugram
EducationNot Mentioned
SalaryNot Disclosed
IndustryIT Services & Consulting
Functional AreaNot Mentioned
EmploymentTypeFull-time

Job Description

    Role Overview:As a Data Scientist in the Marketing team at Google, you will be responsible for driving key measurement and analytics programs that have a substantial impact on Google Marketings media campaigns. You will work on challenging business problems identified by Googles leadership team, analyze data, develop insights, and provide recommendations to senior-level executives. Your role will involve collaborating with cross-functional stakeholders to implement solutions and measure their impact.Key Responsibilities:- Utilize your expertise in data analytics to address marketing challenges and identify optimization opportunities to enhance brand and performance marketing efforts.- Develop measurement plans, tracking requirements, reporting, metrics, and benchmarks for large-scale campaigns to assess the incremental impact of marketing investments, including conversion lift tests, matched market analyses, and brand lift studies.- Collaborate with internal teams on advanced analytics projects involving experimentation, measurement, and modeling.- Implement a customer-centric, data-driven approach based on a people-based marketing strategy to create, segment, and test audiences for optimal business outcomes.- Create evaluation frameworks for models, new metrics, and investigate anomalies, addressing ambiguous problems by prioritizing technical tasks and innovating statistical methods.Qualifications Required:- Masters degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.- 4 years of experience utilizing analytics to solve product or business problems, including coding in Python, R, SQL, querying databases, and statistical analysis.(Note: The additional details of the company were not explicitly mentioned in the job description.) Role Overview:As a Data Scientist in the Marketing team at Google, you will be responsible for driving key measurement and analytics programs that have a substantial impact on Google Marketings media campaigns. You will work on challenging business problems identified by Googles leadership team, analyze data, develop insights, and provide recommendations to senior-level executives. Your role will involve collaborating with cross-functional stakeholders to implement solutions and measure their impact.Key Responsibilities:- Utilize your expertise in data analytics to address marketing challenges and identify optimization opportunities to enhance brand and performance marketing efforts.- Develop measurement plans, tracking requirements, reporting, metrics, and benchmarks for large-scale campaigns to assess the incremental impact of marketing investments, including conversion lift tests, matched market analyses, and brand lift studies.- Collaborate with internal teams on advanced analytics projects involving experimentation, measurement, and modeling.- Implement a customer-centric, data-driven approach based on a people-based marketing strategy to create, segment, and test audiences for optimal business outcomes.- Create evaluation frameworks for models, new metrics, and investigate anomalies, addressing ambiguous problems by prioritizing technical tasks and innovating statistical methods.Qualifications Required:- Masters degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.- 4 years of experience utilizing analytics to solve product or business problems, including coding in Python, R, SQL, querying databases, and statistical analysis.(Note: The additional details of the company were not explicitly mentioned in the job description.)

Keyskills :
AnalyticsPythonSQLExperimental DesignMachine LearningRegressionClassificationRoot Cause AnalysisAudience SegmentationMarketing AnalyticsData ScienceData AnalyticsAutomated Analytics PipelinesPropensity ModelingBayesian ApproachesData Pipe

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