Marketing Mix Modeling Specialist, Large Customer Sales - Singapore, Jakarta, Kuala Lumpur, Ban[...]

GOOGLE ASIA PACIFIC PTE. LTD.; Southwest; On-site; SGD 80,000 - 150,000; Full time

Job summary

An established industry player is seeking a Marketing Mix Modeling Specialist to optimize marketing investments through advanced statistical modeling and data insights. In this pivotal role, you will collaborate with clients to shape their advertising strategies, leveraging your expertise in media analytics and tools like Python and R. This position offers an exciting opportunity to influence decision-making and drive innovation in marketing measurement methodologies. Join a forward-thinking team that values data-driven strategies and fosters a culture of excellence in digital marketing.

Qualifications

• 8 years of experience in media analytics or advertising sales.
• Expertise in Python or R for data analysis and modeling.

Responsibilities

• Lead MMM modeling and analysis using Python or R.
• Advise clients on measurement strategies and build relationships.

Skills

Python

R

Media Analytics

Advertising Sales

Digital Marketing

Statistical Modeling

Communication Skills

Education

Bachelor's Degree

Master's in Statistics, Econometrics, Data Science, or related field

Tools

Statistical Modeling Tools

Job description

Product area

Google's Large Customer Sales (LCS) teams are strategic partners and industry thought leaders to the world's leading brands and agencies. We continuously challenge how customers think about their business and how Google can support growth. We focus on helping these players navigate industry shifts and drive business performance by selling Google's advertising solutions across Search, YouTube, Measurement, and more. As a member of our LCS team, you'll have the opportunity to sell at the forefront of technology, collaborating with executives, influencing strategies, and delivering results that impact global businesses and Google’s growth.

Job description

Businesses partnering with Google vary widely, and no single advertising solution fits all. Your expertise in online media, communication skills, and analytical abilities will shape how these businesses grow. You will provide client service, conduct research and market analysis, and understand client decision-making processes. You will explore their business needs and demonstrate how our products can support their growth. Working with clients, you will set the vision and strategy for their advertising reach.

Additional job description

As a Marketing Mix Modeling (MMM) Specialist at Google, you will help clients optimize marketing investments through statistical modeling and data insights. You will advise on MMM analyses, translate technical results into business strategies, and influence decision-making. You will promote measurement methodologies and foster a data-driven marketing culture within Google and for clients.

Qualifications

Job responsibilities

• Lead MMM modeling and analysis using Python, R, or other tools. Analyze marketing data to identify performance drivers and recommend actions. Explain statistical concepts to technical and non-technical audiences.
• Advise clients on measurement strategies, build relationships with stakeholders, including marketing leaders and agencies.
• Collaborate with sales, product, and customer teams to advance MMM discussions and resolve issues. Develop and implement new measurement methods and tools.
• Identify opportunities to enhance Google's MMM capabilities and drive industry innovation.

Minimum qualifications

• Bachelor's degree or equivalent experience.
• 8 years in media analytics, advertising sales, digital marketing, consulting, or financial analysis.
• Experience with Python or R for data analysis and modeling.

Preferred qualifications

• Master's in Statistics, Econometrics, Data Science, Mathematics, or related field.
• Experience with MMM techniques like Bayesian MMM, time series regression, or machine learning.
• Experience developing MMMs in a business context, with knowledge of regression, time series, and causal inference.
• Understanding of digital advertising and measurement tools (attribution, experiments, data clean rooms, APIs).
• Strong communication skills for presenting complex data to senior stakeholders.