Data Scientist, Google Ads Professional Services team is seeking a Data Scientist to join their team and help clients optimize their marketing efforts through advanced data science and machine learning techniques. In this role, you will directly contribute to the measurement and optimization of marketing ROI for Google’s largest clients by developing tailored models to solve complex business challenges. You will have the opportunity to work at the intersection of marketing analytics, machine learning, and data science, providing actionable insights to clients and helping them leverage Google's products for maximum impact.
Minimum Qualifications
- Master's Degree in a quantitative field such as Statistics, Mathematics, Applied Sciences, or a related field, 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 performing statistical analysis.
Preferred Qualifications
- PhD in Statistics, Mathematics, Economics, Applied Science, or a related field.
- 4 years of experience in applying analytics to solve product or business problems, coding (e.g., Python, R, SQL), and querying databases.
- Experience with Computer Vision and Natural Language Processing (NLP) in marketing analytics.
- Expertise in generative AI technologies and applying them to solve customer marketing problems.
- Experience delivering actionable insights from Machine Learning (ML) models to clients, including problem scoping, modeling, and interpretation.
- Experience using or deploying digital analytics and measurement solutions.
Responsibilities
- Take the lead on the data science aspects of client engagements related to marketing effectiveness and portfolio management. Bring a deep understanding of machine learning (ML) and statistical techniques to develop solutions that address clients' most critical business challenges.
- Work directly with clients to understand their business problems, identify the best statistical techniques to solve these issues, and own the end-to-end development of modeling frameworks that deliver business value.
- Assess data and model readiness for clients, scaling proof-of-concept models to larger, more impactful solutions. Lead efforts to ensure models can be operationalized and deployed at scale.
- Collaborate with internal teams and clients to convert data and model outputs into actionable tactical and strategic insights. Co-present these insights to clients and work alongside them to integrate recommendations into their business processes.
- Work closely with Product and Development teams to enhance and expand the capabilities of Google’s Applied Data Science team. Proactively help drive innovation, explore new methodologies, and ensure that solutions scale efficiently.
Additional Qualifications
- Expert in Data Science Techniques. Deep knowledge of statistical modeling, machine learning, and advanced analytics techniques.
- Client-Facing Skills. Proven ability to communicate complex technical concepts to clients and stakeholders, translate analytical results into business decisions, and influence strategic decision-making.
- Collaboration. Ability to work in a cross-functional environment, collaborating with internal teams, clients, and product developers to deliver impactful data solutions.
Why Google?
- Innovative Culture. Be part of a diverse and innovative team that helps bring cutting-edge technologies to solve real-world challenges for clients.
- Growth & Learning. Google fosters an environment where employees can continuously grow their technical expertise and leadership skills.
- Global Impact. Work on high-impact projects that influence Google's largest clients and contribute to their success in the digital marketing space.
- Inclusive Environment. Google is proud to be an equal-opportunity employer, committed to fostering a diverse and inclusive workplace.
How to Apply. If you’re excited to bring your expertise in Data Science, Machine Learning, and Marketing Analytics to Google and make a significant impact on the digital marketing landscape, we encourage you to apply.