Engineering Analyst Manager, Ads Fraud and Integrity
Google · Bangalore
Collected role description
Role overview
Engineering Analyst Manager, Ads Fraud and Integrity at Google
Required qualifications
- Minimum qualification: Bachelor’s degree or equivalent practical experience.; 7 years of experience developing technical strategy and executing data-driven solutions, including building and managing multi-tiered policy enforcement systems.; 3 years of experience in people management, including mentoring analytical and technical teams (e.g., data scientists, engineering analysts) in applied AI.; Experience translating data analyses and emerging abuse trends into business strategies for non-technical stakeholders and leadership.
Preferred qualifications and skills
- Preferred qualification: 10 years of experience in technical strategy and execute data-driven solutions at scale, including building and managing complex, multi-tiered policy enforcement systems.; Understanding of machine learning lifecycles, human-in-the-loop workflows, precision/recall metrics, and model drift, with the ability to confidently evaluate vendor technical architectures and scale AI-driven defenses.; Excellent communication skills, able to explain complex technical issues clearly to stakeholders at different levels and to influence decision-making across roles.; Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.
Employment details
- Location: Bengaluru [Karnataka] [India]
Application details
- Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy .
About the employer
- Google is proud to be an equal opportunity and affirmative action employer.
- Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
- Please do not forward resumes to our jobs alias, Google employees, or any other organization location.
Additional role details
- We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.
- See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .
- If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
- To all recruitment agencies: Google does not accept agency resumes.
- Google is not responsible for any fees related to unsolicited resumes.
- Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc.
- Alphabet Inc. is your sole contractual partner with respect to equity grants.
- GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement.
- They have no impact on statutory payments.
- Current or past grants do not confer an acquired right.
Collected minimum qualification
Bachelor’s degree or equivalent practical experience.; 7 years of experience developing technical strategy and executing data-driven solutions, including building and managing multi-tiered policy enforcement systems.; 3 years of experience in people management, including mentoring analytical and technical teams (e.g., data scientists, engineering analysts) in applied AI.; Experience translating data analyses and emerging abuse trends into business strategies for non-technical stakeholders and leadership.
Collected preferred qualification
10 years of experience in technical strategy and execute data-driven solutions at scale, including building and managing complex, multi-tiered policy enforcement systems.; Understanding of machine learning lifecycles, human-in-the-loop workflows, precision/recall metrics, and model drift, with the ability to confidently evaluate vendor technical architectures and scale AI-driven defenses.; Excellent communication skills, able to explain complex technical issues clearly to stakeholders at different levels and to influence decision-making across roles.; Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.
Collected experience requirement
7 years of experience developing technical strategy and executing data-driven solutions, including building and managing multi-tiered policy enforcement systems.