Business and Marketing Data Scientist II
Mountain View, California
Employer: Google
Industry: Software Engineering
Salary: $127000 - $187000 per year
Job type: Full-Time
Minimum qualifications:
Preferred qualifications:
About the job
The GCS Data Science team is working on challenging yet interesting problems for Google's Global Business Organization (GBO). Our vision is to build efficient and scalable ML models that help small and midsize businesses around the world to grow their business leveraging the power of Google solutions.
In this role, you will work in close partnership with several Engineering, Product, and Finance teams across Google to develop and deliver machine learning and predictive analytics solutions at scale to our Sales and Marketing stakeholders. You will build recommendation engines and impact measurement tools for Google Customer Solution Sales and Marketing to increase impact and operational effectiveness across the customer journey. You will also build, test, and scale statistical and machine learning models that measure and amplify impact across the entire advertiser journey from acquisition to growth and retention.
Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who maintain a relentless focus on customer success by bringing the best Google has to offer to small- and medium-sized businesses (SMBs), which are the backbone of our communities. As a member of our team, you'll have the opportunity to work with company owners and make a real difference in their businesses by helping them grow. Together, we help shape the future of innovation for customers, partners, and sellers...and we have fun doing it.
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 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
- 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.
- 3 years of experience in Deep Learning, Natural Language Processing (NLP), or Natural Language Understanding (NLU) and frameworks.
Preferred qualifications:
- PhD in a quantitative discipline such as Computer Science, Engineering, or equivalent practical experience.
- 4 years of experience in Deep Learning, Natural Language Processing (NLP), or Natural Language Understanding (NLU) and frameworks.
- Experience in driving a project from an experimental idea to a proof-of-concept to a launched product feature.
- Experience in cross-functional collaboration, with engineering teams and product teams.
About the job
The GCS Data Science team is working on challenging yet interesting problems for Google's Global Business Organization (GBO). Our vision is to build efficient and scalable ML models that help small and midsize businesses around the world to grow their business leveraging the power of Google solutions.
In this role, you will work in close partnership with several Engineering, Product, and Finance teams across Google to develop and deliver machine learning and predictive analytics solutions at scale to our Sales and Marketing stakeholders. You will build recommendation engines and impact measurement tools for Google Customer Solution Sales and Marketing to increase impact and operational effectiveness across the customer journey. You will also build, test, and scale statistical and machine learning models that measure and amplify impact across the entire advertiser journey from acquisition to growth and retention.
Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who maintain a relentless focus on customer success by bringing the best Google has to offer to small- and medium-sized businesses (SMBs), which are the backbone of our communities. As a member of our team, you'll have the opportunity to work with company owners and make a real difference in their businesses by helping them grow. Together, we help shape the future of innovation for customers, partners, and sellers...and we have fun doing it.
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 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
- Collaborate with stakeholders to understand the domain, business goals, and data infrastructure context.
- Solve real-world problems with the latest research in deep learning, natural language processing, and understanding.
- Work with Product teams to understand their objectives, product requirements, constraints, and key metrics.
- Propose, build, evaluate, and debug machine learning models and algorithms.
Created: 2024-09-07
Reference: 141878582182847174
Country: United States
State: California
City: Mountain View
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