Lead Marketing Analyst

We’re looking for a Lead Marketing Analyst to drive the transformation of our marketing analytics in 2026. You will build an end-to-end analytics ecosystem where forecasting, AI agents, and decision-ready BI power paid acquisition scaling and automate repetitive analytical work. We need a true player-coach: someone with a strong technical background who can lead a small team hands-on, set high standards for data and measurement and deeply understands how mobile performance marketing actually works.

Responsibilities

• Own Marketing Analytics strategy for 2026: define roadmap, priorities, success metrics, and execution plan for UA analytics, forecasting, BI and automation.
• Be the analytical counterpart for Performance Marketing leadership: challenge assumptions, build decision frameworks for budget allocation, CAC/LTV/ROI targets, and scaling constraints.
• Lead an analytics team (starting from 2 marketing analysts) as a player-coach: mentor, set standards (SQL style, documentation, dashboards, review process), build sustainable processes and hire as the function grows.
• Build a reliable marketing data foundation: design and implement curated data layers (staging → intermediate → marts) using dbt, orchestrate pipelines and SLAs in Airflow, ensure data lineage, ownership, documentation, and reproducibility.
• Develop UA performance analytics at scale: cohort analytics, ad-level performance deep dives, funnel conversion analysis, geo/segment breakdowns, incrementality where feasible and spend efficiency insights.
• Drive automation with AI-agents: build internal tools/agents that automate routine analysis (alerts, creative diagnostics, anomaly explanations), integrate with OpenAI API/LLM stack, and ensure safe & auditable usage.
• Build and maintain executive BI (Tableau): scalable semantic layer / dashboards that are trusted, fast and actionable.
• Deliver predictive systems: LTV/ROI forecasting, payback modeling, early signals (D0–D3 predictors), scaling scenarios and forecast accuracy monitoring.
• Rethink measurement methodology: improve attribution interpretation, reduce bias, set up consistent evaluation of experiments, creatives, and channel changes.
• Establish Data Governance & Data Quality: define key metrics definitions, single source of truth, automated tests/monitors (freshness, completeness, anomalies), incident workflow and stakeholder-facing metric contracts.
• Cross-functional leadership: work closely with Product, Data Engineering, UA, and Growth to align goals, ensure data availability and turn insights into changes.

Requirements

• Must-have:
• 5+ years in data/marketing analytics with strong ownership mindset.
• 2+ years leading analytics function/projects end-to-end (team lead / tech lead / analytics lead).
• Deep understanding of User Acquisition for mobile apps: funnels, CAC/LTV, creative testing, budget scaling, attribution constraints, cohort behavior.
• Strong Python for analytics/automation (pandas, numpy, visualization, APIs, basic ML as needed).
• Strong SQL skills (ideally ClickHouse or other analytical DBs) and ability to build efficient data models.
• Hands-on experience with predictive modeling / forecasting in marketing or product analytics: cohort-based LTV/ROI forecasting, payback curves; ability to build, validate, monitor, and iterate models in production.
• Hands-on experience with dbt (data modeling, incremental models, testing, documentation) and Airflow (orchestrating pipelines, SLAs, retries, dependencies).
• Strong BI expertise: Tableau (preferred) or similar; ability to design semantic/metric layers and dashboards that stakeholders actually use.
• Proven track record of turning analytics into measurable UA improvements (scaling profitably, improving ROAS, reducing CAC, improving forecast accuracy).
• Strong communication: translate business questions into analytical approaches and defend decisions with data.
• Nice-to-have:
• Experience with SKAN, incrementality testing or causal inference basics.
• Experience with LLM tooling: OpenAI API, prompt/versioning, agent frameworks, evaluation/QA for LLM outputs, safe deployment practices.

How we hire:

• HR interview
• Hiring manager interview
• Final interview
• Reference check

Conditions

• Professional development – paid training and courses, online / offline lectures, workshops and trainings. Our employees take part in all major IT meetups;
• Adaptation – qualitative onboarding, we help to quickly and smoothly solve all problems. regularly collect feedback throughout the trial period;
• Career development – Review is conducted every 6 months, we monitor results and help improve performance;
• Balance between work and personal life – ability to conveniently build your work schedule, take vacations and days off without a bunch of approvals and bureaucracy;
• Health – extended voluntary health insurance (on the territory of Montenegro);
• Office space – a cool office in Montenegro, with comfortable workplaces and lounge areas;
• Relocation – we offer a full package of documents for those who are ready to move to Montenegro, and we help with obtaining a residence permit;
• Prequel+ – premium access to the entire Prequel product.