Senior Measurement Analyst, North America

Responsibilities Collaborate with measurement, product and sales teams to develop and implement measurement and analytical strategies that drive revenue growth. Leverage internal and external data sources to build visualizations and reporting to inform the business and measurement strategies. Track and report advertiser performance metrics to support and grow adoption of measurement solutions, and build dashboards with advanced functionality. Use campaign and business outcomes data, applying statistical models and methodologies to explain the drivers of upper and lower funnel metrics. Design and test bidding, targeting, and optimisation methods to support new product and feature development. Build prototype models, solutions, and applications using tools such as Python and R that can be leveraged by the measurement teams to understand drivers of campaign performance at scale. Provide actionable insights and recommendations to sales and measurement teams to optimise ad campaigns and improve ROI. Conduct training and education for measurement teams on using reporting, dashboarding and analytical solutions. Stay up-to-date with industry trends, best practices, and new measurement methodologies to continuously improve our measurement capabilities. Qualifications Minimum Qualifications: 5+ years of experience in analytics and digital advertising from large marketing-related organisations or measurement suppliers. Bachelor's degree in a quantitative field (e.g., Statistics, Data Science, Analytics, Mathematics, Economics, or Computer Science). Proven experience in Data Science, Data Analysis, Measurement, or a related field, with an understanding of experimentation (conversion lift or geo‑lift), attribution (last or multi‑touch), and modelling solutions (marketing mix modelling). Experience using SQL, Python/R and visualisation solutions on a consistent basis in professional environments. Hands‑on experience conducting advanced analysis using methods such as regression, decision trees, random forests, etc., with a portfolio of applications built using these methods in Python or R. Strong problem‑solving skills, with the ability to interpret complex data sets and communicate insights effectively. Preferred Qualifications: PhD in Statistics or Data Science fields. Experience working in Data Science teams at technology companies focused on marketing and media topics. Familiarity with privacy‑first innovation for marketing measurement systems. Job Information Compensation: The base salary range for this position in the selected city is $121,600 - $220,400 annually. Compensation may vary outside this range depending on qualifications, skills, competencies and experience, and location. Base pay is one part of the total package, and this role may also be eligible for discretionary bonuses, incentives, and restricted stock units. Benefits may vary depending on the nature of employment and country of work location. Employees have day‑one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short‑term and long‑term disability coverage, life insurance, wellbeing benefits, and more. Employees also receive 10 paid holidays per year, 10 paid sick days per year, and 17 days of paid personal time (prorated upon hire with increasing accruals by tenure). The company reserves the right to modify or change these benefit programs at any time, with or without notice. Legal summary for Los Angeles County (unincorporated) candidates: Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information, including proprietary and trade secret information and access to information technology systems;
3. Exercising sound judgement.

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