Business Data Scientist, gTech Ads

1 Month ago • 3-5 Years • Data Analyst

Job Summary

Job Description

This Business Data Scientist role at Google's gTech Ads focuses on measuring and optimizing marketing ROI for major clients. Responsibilities include leading data science aspects of client engagements, collaborating with clients to identify and implement statistical solutions, developing end-to-end modeling frameworks, scaling proof-of-concept solutions, and translating data/model results into actionable insights. The role requires collaboration with internal teams and clients to integrate recommendations into business processes and also involves collaborating with Product/Engineering teams to enhance Applied Data Scientist team capabilities and drive innovation. Deep knowledge of ML and statistics is essential.
Must have:
  • Master's degree in quantitative discipline
  • 3+ years analytics experience solving business problems
  • Proficiency in Python, R, SQL
  • Experience with ML model building and deployment
  • Strong communication & presentation skills
Good to have:
  • 2 years experience delivering ML insights to customers
  • 2 years experience with digital analytics solutions
  • Understanding of statistical algorithms in marketing analytics
  • Proficiency in Computer Vision and NLP for marketing analytics
  • Experience with generative AI in marketing

Job Details


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.

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.
  • Understanding of the statistical algorithms typically used in Marketing Analytics.
  • Proficiency in Computer Vision and NLP in the context of marketing analytics and the ability to bring cutting-edge generative AI technologies to customer issues in marketing.

About the job

gTech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within Google to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with Google and we remain a trusted partner.

We are multi-disciplined professionals, PhDs, statisticians, economists, engineers, and former consultants with deep experience in Data Science, Machine Learning and Marketing Analytics.

In this role, you will be helping in measuring and optimizing marketing Return on Investment (ROI) for Google’s largest clients. You will be building models that address client’s key business issues. You will learn the innovative technologies that drive Google products and bring those innovations to life in the context of specific client needs.

Responsibilities

  • Lead data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management with deep knowledge of ML and statistics.
  • Collaborate with customers to unpack the issues and identify the best statistical techniques that can solve the issues and own the development of end-to-end modeling framework.
  • Engage important stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a large solution.
  • Work with customers and internal teams to translate data and model results into tactical and strategic 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.

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