At Wise. Energy, the Marketing Analytics Specialist is a vital, multi-disciplinary role designed to bridge the gap between complex data infrastructure and high-impact marketing strategy. As the company expands its global footprint across key hubs like Singapore, London, and Hong Kong, optimizing marketing spend and understanding the customer journey becomes increasingly critical. This position does not just sit in a silo; it serves as the analytical engine that powers growth, directly influencing how millions of dollars in marketing budget are allocated.

This role is uniquely positioned as a "unicorn" measurement role. You will not simply build dashboards; you will own the code, define complex attribution logic, design robust experimentation frameworks, and act as a strategic partner to marketing stakeholders. By translating raw data into actionable growth strategies, you will directly impact Wise. Energy's ability to acquire and retain customers efficiently at scale.

Working in this position requires a rare blend of technical expertise and business acumen. You will collaborate closely with engineering, product, and regional marketing teams to build clean data pipelines, implement multi-touch attribution models, and execute marketing mix modeling (MMM). Navigating this fast-paced environment requires adaptability, analytical rigor, and the ability to influence senior leaders with data-driven narratives.

To succeed in the Marketing Analytics Specialist interview process at Wise. Energy, you must prepare for a wide range of questions. These questions are designed to test your technical coding skills, your understanding of marketing measurement frameworks, and your ability to solve complex, ambiguous business problems.

Technical & SQL Queries

These questions evaluate your ability to manipulate data, write clean code, and build structured datasets for analysis.

• Write a SQL query to calculate the monthly retention rate of users acquired through paid marketing channels.
• How do you optimize a slow-running SQL query that joins large clickstream datasets with user conversion tables?

Preparing for the Marketing Analytics Specialist role at Wise. Energy requires a balanced approach. Because this is a multi-disciplinary role, you must demonstrate strength across several core competencies rather than focusing on just one area.

Technical Rigor – You must prove your ability to write production-grade SQL and understand data pipeline architecture. Interviewers will evaluate how cleanly you structure your code and whether you can "own the code" from ingestion to reporting.

Measurement Domain Expertise – You need a deep understanding of marketing technology, attribution logic, and experimentation. Be ready to explain not just the "how" of tracking, but the "why" behind different measurement methodologies.

Strategic Influence – Wise. Energy values analysts who act as strategic consultants. You must show that you can translate complex data points into clear business recommendations that non-technical stakeholders can easily understand and act upon.

Resilience and Ambiguity Management – The team operates in a fast-paced environment where goals and resources can shift. Demonstrating how you navigate ambiguity, handle high-pressure scenarios, and deliver results with limited resources is key to standing out.

The interview process for the Marketing Analytics Specialist position at Wise. Energy is structured to thoroughly evaluate both your technical capabilities and your strategic fit. Candidates generally undergo a multi-stage loop designed to assess different dimensions of the "unicorn" skillset required for the role.

The process typically begins with a recruiter screen to review your background and check alignment on role expectations. This is followed by a hiring manager interview focusing on your past experience, domain knowledge, and strategic approach. Next, you will complete a take-home case study or technical assessment, which you will later present to the hiring team. The final stages involve interviews with cross-functional team members, peers, and a global department lead to evaluate your collaboration skills and leadership potential.

This visual timeline illustrates the typical progression of stages you will encounter during your candidacy. Candidates should use this roadmap to structure their preparation phases, ensuring they dedicate ample time to both the take-home task and the cross-functional presentation. Managing your preparation timeline effectively will help you maintain high performance throughout the entire process.

To excel in the core rounds of the Wise. Energy interview loop, you must understand exactly what the hiring team is looking for in each specific domain.

Technical & Analytics Engineering

This area evaluates your ability to build, maintain, and optimize the data infrastructure that powers marketing insights. You are expected to write clean, efficient SQL and demonstrate a strong understanding of data modeling.

Be ready to go over:

• SQL Optimization – Writing complex queries, using common table expressions (CTEs), window functions, and optimizing joins on massive datasets.
• Data Pipeline Architecture – Understanding how data flows from marketing platforms (e.g., Google Ads, Meta) into a data warehouse and how to model that data for downstream reporting.
• Analytics Engineering Best Practices – Version control, documentation, and maintaining clean codebases to ensure data quality and reliability.

Example scenarios:

• Designing a robust data pipeline to ingest and normalize multi-channel ad spend data.
• Refactoring a legacy SQL query that is causing dashboard latency due to inefficient join logic.

Marketing Measurement & Data Science

This domain focuses on your ability to design scientific measurement frameworks that prove the true value of marketing initiatives.

Be ready to go over:

• Attribution Logic – Designing and implementing multi-touch attribution (MTA) models and explaining their trade-offs compared to single-touch models.
• Experimentation (A/B Testing) – Setting up clean tests, determining sample sizes, managing selection bias, and calculating statistical significance.
• Marketing Mix Modeling (MMM) – Leveraging econometric modeling to understand the high-level impact of marketing channels, including offline media.

Example scenarios:

• Evaluating the incremental lift of a brand campaign using a geo-match testing methodology.
• Adjusting attribution weights to account for cross-device user journeys and cookie deprecation.

Strategic Consulting & Business Case

This area tests your ability to act as a business partner to marketing leaders, helping them optimize budget allocation and solve complex growth challenges.

Be ready to go over:

• Budget Optimization – Recommending budget reallocations across channels to maximize return on ad spend (ROAS) or customer lifetime value (LTV).
• Resourceful Problem Solving – Formulating strategies to achieve aggressive growth targets under tight budget or headcount constraints.
• Stakeholder Communication – Translating technical data concepts into clear, actionable business recommendations for non-technical partners.

Example scenarios:

• Presenting a strategic plan to reverse a downward trend in organic user acquisition.
• Structuring a business case to justify a significant budget increase for a unproven marketing channel.