Performance Marketing Analyst

Traveloka; Indonesia; On-site; IDR 167,400,000 - 390,600,000; Full time

Job summary

Traveloka is seeking a highly analytical professional to join its performance marketing analytics team. This role designs measurement frameworks, builds models, and runs experiments to identify drivers of growth, rather than executing campaigns.

You will work directly with channel owners, pull data with SQL, and present evidence-based conclusions that can shift how success is measured. You will design experiments, build models, and develop self-serve dashboards to empower leadership with

Qualifications

• Bachelor's degree or higher in Data Science, Statistics, Mathematics, Computer Science, or a similar quantitative field.
• 2–6 years of experience in marketing analytics, data science, or a related analytical role.
• Strong statistical foundation — hypothesis testing, regression, causal inference, and experimentation design.
• Hands‑on experience setting up and running your own A/B tests and incrementality studies, not just interpreting results handed to you.
• Proficient in SQL and at least one analytical language (Python or R).
• Experience with marketing measurement concepts (attribution, MMM, incrementality, LTV/CAC) is a strong plus.
• Demonstrated ability to build a point of view from data and defend it, not just report metrics.
• Strong written and verbal communication — able to translate technical analysis into decisions non‑technical stakeholders can act on.
• Experience in digital or performance marketing is helpful but not required.

Responsibilities

• Measure what matters. Design and run experiments (geo holdouts, A/B tests, incrementality tests, lift studies) to isolate the true contribution of marketing spend across channels. Push back on attribution‑based reporting when it overstates impact.
• Build the models. Develop and maintain measurement frameworks — marketing mix modeling, attribution, LTV/CAC analysis — that inform budget allocation and channel strategy.
• Partner, don't just support. Work with performance marketing channel owners to translate business questions into analytical projects, from problem definition through to insight delivery.
• Work the data yourself. Pull, clean, and validate large datasets using SQL. Build repeatable analysis pipelines in Python or R rather than one‑off spreadsheets.
• Build tools, not just reports. Develop dashboards and self‑serve reporting that give channel owners and leadership real‑time visibility into performance, reducing reliance on ad hoc requests.
• Bring the evidence to the table. Present findings to marketing leadership with a clear, evidence‑based point of view — including where the current playbook or measurement approach is wrong.
• Improve the operating rhythm. Identify manual reporting and modeling workflows that should be automated. Partner with data engineering to scale your tools across the team.

Skills

SQL

Python

R

A/B testing

Causal inference

Education

Bachelor's degree or higher in Data Science/Statistics/CS

Tools

SQL

Job description

Job Description

This role sits inside performance marketing, but the mandate is analytical. You will build the measurement frameworks, models, and experiments that tell us what is actually driving growth — not run campaigns day-to-day. You will partner closely with channel owners, but your core output is analysis: rigorous, evidence-based, and defensible under scrutiny.

You will not be handed a dashboard and asked to summarize it. You will be expected to design the experiment, build the model, pull the data yourself, and form a point of view that challenges how we currently measure success.

We're evolving how this team works — sharpening how we measure and scale growth. This is a hands‑on opportunity to help shape that shift, not just run the existing playbook.

How You Will Work

You will operate with a clear analytical mandate and high accountability. We expect you to form hypotheses, test them rigorously, and update your point of view based on what the evidence shows. You will have direct access to senior leadership through regular reviews, and your models and analyses will inform decisions on where the company invests its growth capital.

We are not looking for someone who reports metrics. We are looking for someone sharp enough to question the measurement itself, structured enough to build a better model, and credible enough to change how the business decides.

Job Responsibilities

• Measure what matters. Design and run experiments (geo holdouts, A/B tests, incrementality tests, lift studies) to isolate the true contribution of marketing spend across channels. Push back on attribution‑based reporting when it overstates impact.
• Build the models. Develop and maintain measurement frameworks — marketing mix modeling, attribution, LTV/CAC analysis — that inform budget allocation and channel strategy.
• Partner, don't just support. Work with performance marketing channel owners to translate business questions into analytical projects, from problem definition through to insight delivery.
• Work the data yourself. Pull, clean, and validate large datasets using SQL. Build repeatable analysis pipelines in Python or R rather than one‑off spreadsheets.
• Build tools, not just reports. Develop dashboards and self‑serve reporting that give channel owners and leadership real‑time visibility into performance, reducing reliance on ad hoc requests.
• Bring the evidence to the table. Present findings to marketing leadership with a clear, evidence‑based point of view — including where the current playbook or measurement approach is wrong.
• Improve the operating rhythm. Identify manual reporting and modeling workflows that should be automated. Partner with data engineering to scale your tools across the team.

What We're Looking For

• Bachelor's degree or higher in Data Science, Statistics, Mathematics, Computer Science, or a similar quantitative field. Candidates from strong, reputable universities preferred.
• 2–6 years of experience in marketing analytics, data science, or a related analytical role.
• Strong statistical foundation — hypothesis testing, regression, causal inference, and experimentation design.
• Hands‑on experience setting up and running your own A/B tests and incrementality studies, not just interpreting results handed to you.
• Proficient in SQL and at least one analytical language (Python or R).
• Experience with marketing measurement concepts (attribution, MMM, incrementality, LTV/CAC) is a strong plus.
• Demonstrated ability to build a point of view from data and defend it, not just report metrics.
• Strong written and verbal communication — able to translate technical analysis into decisions non‑technical stakeholders can act on.
• Experience in digital or performance marketing is helpful but not required.