Senior Programmatic Trader (m/f/d)

Kayzen is the Apps DSP: an AI-native platform built on its own bidding engine, for buying app inventory across mobile and connected TV screens. App developers, agencies, media buyers and ad platforms use Kayzen to drive full-funnel outcomes across both screens, from awareness and consideration to installs, purchases and calls. Available through self-serve and managed services, Kayzen combines machine-learning optimisation with bid - and impression-level transparency, granular control over buying decisions, and AI capabilities that connect campaign data to the AI assistants teams already use. Kayzen’s vision is to democratise programmatic marketing by making it accessible to every team. Headquartered in Berlin, Kayzen operates globally.

The Trading team is responsible for creating growth through the management and optimization of mobile performance advertising campaigns for clients utilizing the managed service offering. The goal of the team is to deliver on the client's objectives through established or new trading best practices and communicate account status regularly and effectively with their CSM counterparts. 

In this role, you will own and grow a portfolio of mobile programmatic campaigns (UA/RT) across verticals including gaming, fintech, betting, and CTV, delivering CPA/ROAS targets while scaling FCT and protecting contribution margin. You'll pair deep trading skills with analytics (SQL must have / Python desirable. What matters most: the analytical instinct to ask the right questions and the resourcefulness to find answers, whether through code or AI tools) and LLM-accelerated workflows to move faster than a traditional desk. You won't just optimize campaigns, you'll shape the tools, analytical frameworks, and trading playbooks the team uses to win.

• Own end-to-end campaign delivery across multiple advertisers; hit KPI targets (CPA, ROAS, retention) and scale when unit economics allow.
• Develop audience targeting strategies and supply-side optimization (audience, publisher selection, bid shading, dayparting) across ad formats (banner, video, native, CTV) to unlock incremental scale.
• Build and execute testing roadmaps (optimization models, bids, budgets, frequency, creatives, geos, etc.) to drive incremental lift.
• Manage pacing, budget allocation, and risk across an account book, proactively mitigating under-delivery.
• Understand mobile attribution dynamics (postback flows, attribution windows, deterministic vs probabilistic matching, iOS privacy frameworks) and how they shape bidding strategy, audience targeting, and performance interpretation across MMPs.
• Champion process improvements, author tools/queries, and mentor juniors to raise team throughput.

• Dive into log-level and aggregated data to diagnose performance; write production-grade SQL (joins, CTEs, window functions) and Python/pandas analyses (or sharp use of AI)
• Design and interpret tests, translating findings into the Trading Playbook.
• Leverage LLMs (GPT/Claude) to automate recurring analyses (bid curves, cohort reads, anomaly triage), create data briefs, and draft experiments.
• Contribute to internal dashboards and trading intelligence tools that accelerate decision-making across the team.

• Partner with CSM/Sales on growth plans and QBRs; influence Product with crisp, quantified feedback; collaborate with Supply on inventory quality.
• Work with DS/DA on model inputs, new testing hypotheses or model improvements, and with Product Support to quickly unblock delivery.

Since I am based in Argentina and other key product and customer success team members are located mostly across EMEA and India, we are open to a remote setup of this position. For optimal overlap with customers’ time zones and internal teams your main working location should preferably be close to the CET time zone.

• 3–5 years of programmatic ad buying experience; mobile in-app DSP experience preferred.
• Hands-on with MMPs (AppsFlyer, Adjust, Singular), postback flows, fraud detection, and reporting tools.
• Data-driven decision making; comfortable building and modifying SQL queries (joins, CTEs, window functions a plus). Familiarity with BI tools. Familiarity with AI is a must.
• Nice-to-have: Python/pandas for ad-hoc analyses and light automation; experience is a plus but not required.
• Nice-to-have: CTV/OTT programmatic buying experience.
• Solution orientation and drive to succeed.
• Communication: crisp written analysis and cross-team collaboration. Client-facing confidence preferred.