Marketing Data Scientist

Key Skills

Aartificial intelligence, Analytical and Problem solving, Data science techniques, GTM, Machine learning techniques, Marketing Strategy, Python Programming, R Programming, SQL

Job Description

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
• Experience articulating business questions, using analytical methods to arrive at an answer using available data and selecting the right statistical tools.

Preferred qualifications:

• Experience in applied statistics, including expertise in sampling methods, experimental design, or causal inference techniques.
• Experience working with First-Party data, secondary market data, and Third-Party survey data.
• Ability to work cross-functionally with technical and business stakeholders with excellent listening, critical thinking, and problem solving skills.

About the job

As a data scientist you will develop and improve data sets, pipelines, and analysis tools that deliver actionable insights to help marketers drive business decisions. You will bring scientific accuracy and statistical methods to the challenges of data analytics, interpretation of insights, advertising effectiveness, and content consumption.

This role is focused on generating insights and creating systems that ingest, classify, and transform internal data and perform advanced analytical analysis on both internal and external datasets to enable scaled qualitative and quantitative research within Google Marketing. Your solutions will empower the global marketing team to understand consumer needs, inform our Go-to-Market strategy and campaigns.

You will use programming languages to collect and analyze data as well as machine learning and AI tools to help advance the projects and develop new capabilities. You will prototype and build data pipelines iteratively to provide insights at scale that will be shared through external reports and internal dashboards. You will develop comprehensive knowledge of Google systems and data, advocating for changes where needed for product development. In the course of this work you will be gathering data and system requirements, processing large data sets, performing ongoing analysis, and making presentations.Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems--from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can--changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.

The US base salary range for this full-time position is $127,000-$187,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Solve difficult, non-routine analysis problems, applying advanced analytics methods and models as needed.
• Combine/integrate additional data sources into existing data sets and perform new, impactful calculations.
• Create and track metrics describing the quality of data produced by pipelines. Be proactive in identifying quality issues, ensure they are visible to the appropriate stakeholders, and drive the resolution process.
• Provide research and analytical thought leadership by designing and recommending new analyses, infrastructure, or experiments, to drive improvements in the business.
• Prioritize requests and work well in an environment with competing demands from multiple stakeholders.