Tameson
Marketing Analytics Specialist
About this role
About us Tameson is a global e-commerce business helping SMEs source industrial components. We are looking for a Marketing Analytics Specialist to join our Data Analytics team and bring statistical rigor to how we run and measure paid advertising. The role This is a data-oriented ownership role, not a simple marketing role. We want a paid platform owner with a quantitative background who has worked extensively with paid advertising data, not a media buyer or campaign manager who has picked up SQL along the way. If your strengths are creative strategy, platform certifications, or campaign execution, this role will not fit. You will work directly with the Data Analytics Lead and Marketing Lead in a team that sits at the center of how Tameson makes decisions. Your output will materially shape where marketing budget goes, how we measure its return, and how we test new ideas. A flavor of recent work
- Built a Markov-chain multi-touch attribution model to improve our early-funnel bidding in paid ads channels.
- Built LTV and cohort retention models that let us value customer segments differently, and feed those values back into bidding and targeting.
- Designed and ran A/B and CRO experiments to validate channel changes, on-site changes, and bidding strategies.
- Built the BigQuery and Google Data Studio reporting layer that the business actually uses to track CAC, POAS, and LTV.
- Designed an experimental framework to measure incremental effect of paid advetisement spend. What you would pick up
- Extend and improve our attribution work, challenge assumptions, try alternative models, quantify uncertainty.
- Take full ownership of our paid advertisement strategy, based on data insights and experimental results.
- Design experiments end-to-end: A/B, geo, holdout, CRO. All with proper power analysis, randomization, and evaluation.
- Build models that inform capital allocation across channels: saturation curves, diminishing returns, MMM, for example.
- Analyze complex datasets across customer journeys, search query data, marketplace performance, and CRM.
- Develop customer and audience models that inform who we should target, where, and how much we should pay to reach them. Requirements What We Are Looking For
- Background in a quantitative field: Statistics, data science, physics, computer science or similar. A university degree in one of these is strongly preferred; a strong demonstrable track record can substitute