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.