The role
From Google's own posting.
The gTech Ads LCS team is a team of solution-oriented trusted advisors supporting the biggest and most complex advertisers. Our consultative services take our deep technical and product expertise and combine it with our powerful understanding of customer’s needs and goals to solve their biggest business challenges allowing them to grow and get the most out of Google solutions.
In gTech Users and Products (gUP), our mission is to advocate for Google’s users by creating helpful and trusted experiences across the product ecosystem. We achieve this by meeting partners and consumers where they are with support and help, representing their needs with our product partners and proposing fixes and features that elevate their engagement with Google's diverse product ecosystem. Additionally we provide a range of product services that ensure our products are optimized for every user, no matter where they are in the world (e.g., localization, digitization, partner integration and more). Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Netherlands: €126000 - €129000 (EUR) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
Lead data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management with expertise in ML and statistics.
Collaborate with customers to unpack the issues, identify the best statistical techniques, and own the development of a modeling framework.
Engage important stakeholders to assess data and model readiness and to scale a proof-of-concept to a large solution.
Work with customers and internal teams to translate data and model results into tactical insights that are actionable for decision-making. Co-present to and work with clients to integrate recommendations into business processes.
Collaborate with Product/Engineering teams to increase and optimize capabilities of our Applied Data Scientist (DS) team, employing methods which create opportunities for scale, proactively helping to drive innovation.
Minimum qualifications:
Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R), querying databases (e,g., SQL), or statistical analysis.
Experience in cross-functional program/project management, operational process execution, vendor team management, operations hubs, or distributed operational workflows.
Preferred qualifications:
2 years of experience delivering insights from ML to customers (problem scoping/definition, modeling, interpretation).
2 years of experience using or deploying digital analytics and measurement solutions.
Experience forecasting demand or volume in an operations, contact center, workforce management, or supply chain context; or familiarity with support operations metrics (SLA, AHT, Shrinkage) and capacity planning and staffing methodologies (e.g., Erlang C).
Proficiency in Computer Vision and NLP in the context of marketing analytics and the ability to bring generative AI technologies to customer issues in marketing.
Understanding of the statistical algorithms typically used in Marketing Analytics.
Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R), querying databases (e,g., SQL), or statistical analysis.
Experience in cross-functional program/project management, operational process execution, vendor team management, operations hubs, or distributed operational workflows.