Minimum qualifications:
- Bachelor's degree, or equivalent practical experience.
- 1 year of experience in a Data Science field.
- Master's degree in Statistics, Mathematics, Bioinformatics, Economics, another quantitative field, or equivalent practical experience.
- Experience with data extraction and modeling tools (SQL, Python).
- Experience delivering insights from AI/ML and statistical solutions to clients, including problem scoping/definition, modeling and interpretation.
- Experience with statistical software (such as Python, R or MATLAB) and database languages (such as SQL) with understanding of Artificial Intelligence/Machine Learning (AI/ML).
- Understanding of the statistical algorithms typically used in Marketing Analytics.
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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.
Responsibilities
- Lead data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management with deep knowledge of Machine Learning (ML) and statistics.
- Collaborate with customers to unpack their problems and identify the best statistical techniques that can solve the problem and own the development of modeling framework.
- Engage stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a larger 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 Science team, employing methods which create opportunities for scale, proactively helping to drive innovation.