Kayzen

• Form a deep understanding of the client’s business & goals • Provide DSP advisory and strategic consultation from the onboarding phase • Maintain detailed internal documentation of client information (Hubspot), interactions (call notes), feature requests (product wishlist), and campaign strategies • Conduct engaging and informative Quarterly Business Reviews focusing on learnings, growth opportunities, and evangelizing on product roadmap • Co-manage and optimize campaigns with the Client or Trading team, analyzing aggregate performance and log-level data to improve strategies. • Report on account progress weekly / bi-weekly to internal and external stakeholders (client, PSS Lead, Product teams, etc) • Set and achieve monthly and quarterly growth and milestone targets together with your Team Lead. • Owning end-to-end client success and results through proactive optimizations, troubleshooting, and coordination • Proactively identify and address emerging client needs • Work closely with the product team on enhancements based on client feedback. • Efficiently troubleshoot issues and communicate them to the product and technical teams • Provide regular feedback to management about client needs, market & competitor intelligence

• Enhancing Models: Continuously improving existing models by incorporating new features, fine-tuning parameters, and utilizing additional data. • Algorithm Development: Collaborating with our Machine Learning Engineering team to develop and deploy scalable supervised and unsupervised learning algorithms. • Data Exploration: Identifying and exploring new data sources while researching innovative ways to leverage both new and existing data effectively. • Solution Research: Investigating new Machine Learning solutions to optimize every step of our value chain. • A/B Testing: Regularly conducting and evaluating A/B tests to drive insights and refine our strategies.

• Design, build, and maintain high-quality features across the Fullstack stack, from UI to API integration • Write clean, well-tested, production-ready code and actively participate in code reviews • Collaborate closely with Product, Design, QA, and Backend teams to deliver cohesive, user-centric features • Contribute to technical decisions around architecture, tooling, and best practices within the team • Take ownership of features end to end, from planning through deployment and monitoring • Integrate AI-powered coding agents and automated LLM-based testing into your daily development cycle • Contribute to building 'AI-First' UI patterns, working alongside the LLM Platform team on generative, prompt-driven interfaces • Stay current with emerging AI-assisted development tools and bring relevant ones back to the team • Break down assigned product requirements into clear, actionable engineering tasks • Deliver work reliably within sprint commitments, flagging blockers or scope changes early • Balance new feature delivery with addressing technical debt in the codebase you work on

• 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.

• Manage day-to-day campaign optimization across a set of advertisers; monitor and hit KPI targets (CPA, ROAS, retention) with guidance from senior traders. • Execute supply-side and audience optimization tactics including publisher management, bid adjustments, and dayparting across ad formats (banner, video, native, CTV). • Run A/B tests on bids, budgets, creatives, and geos as part of broader testing roadmaps; document results and contribute learnings to the Trading Playbook. • Monitor pacing and budget allocation daily, flagging risks and under-delivery proactively. • Build a working understanding of mobile attribution (postback flows, attribution windows, MMP integrations) and how attribution models affect how we measure and optimize campaign performance. • Use SQL to pull and analyze campaign data from internal databases; build comfort with joins, CTEs, and window functions over time. • Learn to leverage LLMs (GPT/Claude) for recurring analyses, data briefs, and performance diagnostics, this is a core part of how our team works. • Support the creation and maintenance of dashboards and reporting tools used by the trading team. • Develop your analytical instincts: learn to ask the right questions, understand what's driving performance, and use available tools (SQL, AI, BI tools) to find answers. • Work with CSMs to understand client goals and communicate campaign status clearly. • Support QBR preparation and client-facing deliverables alongside senior traders. • Collaborate with Product Support to troubleshoot delivery issues and with Supply on inventory quality questions.

• Own and continuously develop Kayzen’s GDPR compliance programme as an AdTech company operating across multiple jurisdictions, with a particular focus on EU and US privacy frameworks • Advise on data processing agreements, privacy notices, consent frameworks, and cross-border data transfers • Act as primary point of contact for internal privacy questions • Provide legal counsel on T&Cs and related transactions • Lead or support contract negotiations with clients and vendors, including MSAs, SaaS agreements, partnership agreements, and NDAs • Ensure commercial contracts are legally robust and aligned with company risk appetite • Manage and maintain Kayzen’s cap table • Oversee corporate governance across Kayzen’s group structure, including subsidiary management, shareholder resolutions, and notarial filings under German law • Support fundraising and investor relations from a legal and corporate perspective • Further develop and scale Kayzen’s compliance framework to match our growth as an internationally operating company • Monitor relevant regulatory developments (ad-tech, data privacy, employment, corporate) and translate them into actionable guidance for the business

• Develop and maintain automated provisioning pipelines (PXE, ZTP) to deploy bare-metal servers ( configure hardware, peripherals, services, settings, directories, storage, etc. in accordance with standards and project/operational requirements) at scale across global data centers. • You research and recommend innovative and automated approaches for system administration tasks. • You perform regular security monitoring to identify any possible intrusions. • You repair and recover from hardware or software failures, coordinating with impacted teams. • You apply OS patches and upgrades on a regular basis, and upgrade administrative tools and utilities. • You maintain data center environmental and monitoring equipment. • You perform ongoing performance tuning, hardware upgrades, and resource optimization as required. • Act as a technical lead and trusted point of contact for the infrastructure team, helping drive operational excellence and engineering best practices. • Support mentoring and onboarding of engineers, improve team collaboration and communication, and contribute to scaling the team as the infrastructure organization grows. • Report directly to CTO while partnering closely with other tech teams to improve reliability, automation, monitoring, and incident response processes across the infrastructure stack.

• Work closely with the C-Suite to develop and execute GTM strategies for growing our business with our target ICPs • Build and maintain strong relationships with industry contacts such as partners, select key customers and suppliers, and multipliers who can help us amplify our message • Predictably and systematically grow our inbound leads and MQL (Marketing Qualified Leads), using effective demand generation approaches (for example, through growing the user base our free kAI Explorer AI Agent) • Deeply empathise with existing and prospective clients to understand their needs and perspectives, analyze and understand industry trends and translate that into building best-in-class messaging and positioning for Kayzen • Ownership and effective use of our suite of marketing tools and systems, such as Hubspot, Wordpress, Claude AI, Fin. • Build a lean but high performing team of marketing specialists focused on driving measurable revenue growth

• Proactively identify and map out potential customers who are large and well-known app developers • Conduct in-depth market research to define target audiences and key decision-makers • Craft personalized outreach messages via LinkedIn, email, and calls to generate interest and schedule meetings • Maintain a high volume of outbound activity (e.g., emails, calls, LinkedIn messages) while focusing on quality engagement • Develop and maintain strong relationships with prospects by understanding their strategy, needs, challenges, and budgets to assess product relevance • Analyze market trends, competitor activities, and customer needs to refine outreach strategies • Keep company CRM tools up to date and ensure records are well maintained

• Apply a broad range of analytical techniques to derive actionable insights from rich product and event data • Work closely with the product team as a data-driven advisor and partner on strategic decisions and roadmap prioritisation • Conduct deep-dive analyses on product performance, user behaviour, and funnel metrics to identify improvement opportunities • Translate complex data findings into clear, concise narratives for technical and non-technical stakeholders • Serve as the go-to person to analyse, debug, and resolve product issues in collaboration with engineering, Product and Business • Go deep into complex customer-facing issues, identify root causes in data, and drive resolution with product and engineering teams • Become a product and domain expert in RTB (Real-Time Bidding) and the broader programmatic advertising ecosystem • Leverage LLMs (GPT/Claude and similar tools) to automate recurring analyses, anomaly triage, data briefs, and BI request resolution — this is a mandatory part of how we work • Build and maintain tools, scripts, and automated pipelines that reduce manual investigation effort and speed up response times • Manage and resolve Business Intelligence requests; develop reusable tools to automate high-frequency reporting needs • Contribute to internal dashboards and analytical tooling that accelerate decision-making across teams • Partner with engineering, data, customer success, and product teams on data-related initiatives and ad-hoc investigations • Provide ideas and quantified feedback for product and process improvement • Champion data quality, accuracy, and a culture of evidence-based decision-making across the organisation