Job summary
Job post source
This job is directly from Zenith
Job overview
The Media Data Scientist role at Zenith involves designing and implementing statistical and machine learning models to link marketing efforts to business outcomes, supporting data-driven decision-making for clients.
Responsibilities and impact
The Data Scientist will design, tune, and maintain advanced models, analyze and interpret data, present insights to business teams, and prepare data for analysis and reporting to optimize client marketing strategies.
Compensation and benefits
The position offers an annual salary range of $72,390 to $109,480, with benefits including medical, dental, vision, disability, 401(k), paid time off, parental leave, family care leave, tuition reimbursement, and flexible time off.
Experience and skills
Candidates need 1+ years of quantitative analysis experience, proficiency in SQL and R, strong statistical and modeling knowledge, and good communication skills; familiarity with marketing analytics and machine learning techniques is preferred.
Career development
Zenith supports professional growth through exposure to emerging technologies, diverse media channels, and advanced analytics methodologies within a leading global media agency.
Work environment and culture
Zenith values diversity, equity, and inclusion, fostering a collaborative environment that celebrates differences and supports employee well-being and growth.
Company information
Zenith is a full-service media agency under Publicis Media, known as 'The ROI Agency,' focusing on driving measurable business outcomes for major global brands.
Team overview
The Data Scientist will work closely with the Data Science Manager and collaborate with Business Planning and Analytics teams to execute data science solutions for client accounts.
Application process
Applicants should submit their applications by June 4, 2025, and can request accommodations during the application or onboarding process via a specified email contact.
Unique job features
This role offers the chance to work with advanced statistical models and machine learning in a media agency setting, with a focus on real-world business impact and client-facing presentations.
Company overview
Zenith is a renowned Swiss watchmaker known for its precision timepieces and innovative craftsmanship. Founded in 1865 by Georges Favre-Jacot, the company has a rich history of pioneering advancements, including the creation of the first integrated automatic chronograph movement, the El Primero, in 1969. Zenith generates revenue through the sale of luxury watches, which are highly regarded for their quality and accuracy. The brand's commitment to excellence and innovation has solidified its reputation in the horology industry.
How to land this job
Position your resume to highlight your expertise in statistical modeling, machine learning, and data analysis, emphasizing experience with R, SQL, and advanced marketing analytics like Marketing Mix Modeling (MMM).
Focus on showcasing your ability to translate complex data into actionable business insights and your strong communication skills, especially your experience presenting analytical results to diverse audiences.
Apply through multiple channels including Zenith’s official careers page, LinkedIn, and relevant job boards to maximize your application’s visibility.
Connect with current Data Scientists or Analytics team members at Zenith on LinkedIn; use ice breakers like commenting on recent projects they’ve shared, asking about their experience working on media data models, or expressing enthusiasm for Zenith’s ROI-driven approach.
Optimize your resume for ATS by incorporating keywords from the job description such as ‘statistical modeling,’ ‘machine learning,’ ‘R programming,’ ‘SQL,’ ‘customer segmentation,’ and ‘Marketing Mix Modeling’ to ensure it passes automated screenings.
Use Jennie Johnson’s Power Apply feature to automate applying across multiple platforms, tailor your resume for ATS, and identify LinkedIn connections to network with, saving you time and increasing your chances of landing the role.
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