Data Science Manager, gTech Ads Solutions

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
• 3 years of experience as a people manager within a technical leadership role.

Preferred qualifications:

• Experience in leading and evolving high-caliber data science and engineering teams with diverse technical strengths.
• Experience preparing and delivering presentations to executive leadership.
• Ability to operate in a complex, cross-functional organization where collaboration with other teams is essential to the success of your team.
• Ability to adept at distilling complex analyses into data driven narratives.
• Excellent communication skills, especially in communicating technical and statistical concepts clearly and concisely among audiences at many different levels.

About the job

As a Data Science Manager in the Measurement Centre of Excellence, you will lead a team of technical experts, utilizing Google’s ML capabilities to build data science and measurement solutions to our Large Customer Sales (LCS) clients. You will closely collaborate with clients, agencies and internal teams.

In this role, you will be responsible for leading a team of data scientists in applying best data science practices to solve our ads customers’ complex problems in marketing. You will be responsible for building and executing gTech’s strategy and outlook to deliver applied data science to Google's largest ads customers, utilizing the best of Google’s ML capabilities to build innovative solutions that address our customer's problem-space.

Responsibilities

• Lead a team of Data Scientists responsible for delivering data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management.
• Develop a data science roadmap for your team that aligns with Data Science strategy and Objectives and Key Results (OKRs). Establish project goals, align individuals' expectations, coordinate resources, and provide technical leadership in-line with the long-term objectives.
• Provide analytical thought leadership in the areas of Data Science and Measurement through proactive and strategic contributions.
• Influence stakeholders through effective presentations and written communication.
• Collaborate with Product/Engineering teams to increase and optimize capabilities of the Applied DS team, employing methods which create opportunities for scale, and help to drive innovation.