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Open nowFirst seen 3 days ago

Business and Marketing Data Scientist II

Google3,473 open roles

Where
Chicago, IL, USA; Austin, TX, USA; Kirkland, WA, USA; Seattle, WA, USA
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Your applicationOpen nowBusiness and Marketing Data Scientist IIGoogle · Chicago, IL, USA; Austin, TX, USA; Kirkland, WA, USA; Seattle, WA, USA

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 29 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: first seen 3 days ago

Google median: 29 days open

The posting

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Chicago, IL, USA; Austin, TX, USA; Kirkland, WA, USA; Seattle, WA, USA.

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, or a relevant PhD degree.
  • Experience developing generative AI solutions at a law firm, in-house legal/compliance department, or within government.

Preferred qualifications:

  • 4 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.

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 Business Data Scientist, you will help the Business Intelligence Group (BIG) enable a more data-driven/predictive Global Affairs organization. Generative Artificial Intelligence (GenAI) is poised to make a significant impact in Global Affairs. With the power of ML/AI and the knowledge of Google tools and technologies, your goal is to leverage the GA data ecosystem to drive decisions for cross-GA strategic initiatives and boost business operations. In this fast-paced and innovative environment your technical expertise will have a direct impact on shaping our AI strategy.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Support the development and implementation of data-driven solutions, with a focus on large language models (LLMs) and AI, to address business problems in Global Affairs, including providing trusted advice to policymakers, building an industry-leading regulatory and compliance system, and protecting our ability to provide high-quality products.
  • Work with cross-functional teams to address AI/ML challenges and opportunities, specifically leveraging LLMs for text analysis and knowledge extraction, and translating business needs into actionable analyses and evaluation metrics.
  • Stay current on emerging trends and best practices in data science and business analytics, with guidance.
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