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Salary
≈ $37k – $75k per year (Estimated)
Location
In office (Singapore)
Seniority
Junior · 2+ years exp

Confirmed on the employer's own hiring board on Oct 9, 2026. First seen by Alion on Oct 7, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

As a Data Science and Analytics Specialist, you will possess a strong technical and coding foundation-specifically in SQL, Python, or equivalent, and data pipeline management-and are eager to apply these skills within the domain of consumer insights (market insights for our Marketing organization). You will bridge the gap between traditional market research and data analysis. You will focus on completing tasks within the scope of larger analytical outcomes, utilizing an analytical mindset to manage large, complex datasets.

Your contributions will be direct and task-oriented, operating under the general guidance of a manager or senior researcher. Google will provide you with comprehensive training and mentorship in market research methodologies, primary/secondary data analytics, and the art of building compelling insight narratives. You will assist in the research and application of data-driven insights that have a tangible impact on marketing performance, such as business case development and trend analysis.

Responsibilities

  • Execute research and analysis tasks within the scope of broader, mission-critical marketing projects.
  • Select appropriate research or analysis methods, tools, and processes from options provided by senior team members to address specific technical challenges.
  • Support senior key decision-makers by delivering research and analysis insights that clarify implications for projects, programs, or services.
  • Assist in conducting research and measurement to support and improve overall marketing performance and organizational thinking.
  • Utilise AI capabilities (e.g. Jetski) to create tools as required for the communication or analysis and reporting of key product or marketing metrics.

Qualifications

Minimum qualifications:

  • Bachelor's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • Experience in statistical (e.g., R, S-Plus, SAS, Python or similar) and database software (e.g., SQL or equivalent).

Preferred qualifications:

  • 2 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
  • Foundational experience with data visualization tools (e.g., charts, graphs, dashboard creation), and interest or foundational training in market research methodologies (quantitative and qualitative).
  • Understanding of the full market research lifecycle, including working with external agencies, drafting RFPs, and reviewing survey questionnaires or discussion guides.
  • Ability to critically evaluate data and translate technical analytics into non-technical, persuasive business reports and commentary.
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