Data Analyst

About us

Love, Bonito is Southeast Asia’s leading womenswear brand, built with a mission to empower women to find confidence through style. Incorporated in 2010 in Singapore, we’ve since grown from a humble online startup into a multi-channel business with over 20 stores and counting across Asia and a thriving online presence.

For the next decade, we are looking to expand through new categories, markets, wholesale partnerships, and brand acquisitions. We are evolving into a next-generation regional consumer group — one that blends heart with performance, and creativity with technology.

At our core, we’re a team of builders, dreamers, and doers who believe culture is more than words on a wall — it’s how we show up every day. We move fast, stay curious, and take bold bets on ideas and people we believe in. Here, you’ll find a community that challenges you to grow, trusts you to lead, and celebrates you for being you. Together, we’re shaping the future of Asian brands — from right here in Southeast Asia, to the world. 

Why join us?

At Love, Bonito, you’ll do more than just a job — you’ll help build a movement. We’re creating an organization that’s lean, bold, and full of heart — where every person has the space to make an impact. Here’s what you can expect:

• Purpose with performance: We’re building a world-class Asian brand that competes globally. We hold ourselves to high standards and operate with purpose, integrity, grit and excellence. Join us if you take customer service excellence seriously and are passionate about creating real impact!
• Growth that’s real: We are known to be incredibly dynamic and fast-paced. You’ll be expected to learn fast, stretch beyond your comfort zone, and work alongside people who challenge and support you in equal measure. Don’t join us if you’re looking for a comfortable, fully structured setup, but do join us if you’re excited to build, shape, and make an impact together!
• Culture at our core: If you’re looking for a no-corporate-BS environment, you’ll fit right in. We lead with empathy, celebrate individuality, and believe that great work comes from trust, not titles. We believe in teamwork and effective collaboration - because when we run together, we go further. If this speaks to your values, come join us and be part of #TeamLB!

Join us as we redefine what it means to build an enduring global consumer group.

About the role

Reporting to the Senior Data Manager, this role is based in ID and owns the analytical backbone of how Love, Bonito makes decisions – from self-serve reporting to forecasting models that tell us what to expect and where to focus next.

Main responsibilities

1. Dashboard & Reporting

• Design, optimize, and maintain performance dashboards that enable stakeholders to explore data independently
• Define and own the metrics layer (clear, documented definitions) so numbers  don’t silently diverge across teams

2. Forecasting & Modeling

• Build and ship production-grade forecasting models for run-rate and sales-event performance, tracked against actuals
• Use forecasting output to inform campaign mechanics

3. Customer Analytics

• Build and maintain customer segmentation and market basket analyses to uncover cross-sell opportunities
• Deliver reusable, scalable analytical frameworks, not one-off answers to one–off questions

4. Governance

• Own model documentation: assumptions, limitations and decision boundaries for any model that influences spend decisions

5. Technical Optimization

• Evaluate and optimise aggregation tables for performance and scalability
• Automate recurring workflows to reduce manual effort and reduce time-to-insight

6. Documentation & Knowledge Management

• Document data models and business logic so solutions are maintainable by other team members and usable as context by internal AI tooling

Who We Are Looking For:

We're hiring for rigor and trajectory – either path below is a fit:

Path A — Applied Quant/Model Shipper:

• Statistical first-principles grounding: understands identification assumptions, confounding, and bias-variance tradeoffs well enough to choose a method because it fits the problem, not because it's the default reach
• Has shipped at least one model or evaluation pipeline to production and can speak to what broke, how it was monitored, and how false positives were ruled out

Path B — Strong Fundamentals Generalist:

• Rigorous quantitative background (statistics coursework, thesis, competitions, or internship work requiring real analytical judgment, not just dashboarding)
• Fast learner with evidence of picking up new methods independently; expected to grow into production modeling on the job

Required for both paths:

• Strong proficiency in Python, SQL, statistics
• Self-starter who proactively finds and closes optimisation gaps
• Comfortable using modern analytics/AI tooling to move faster — no dedicated ownership of agent infrastructure expected
• Collaborative team player who takes ownership and drives projects to completion

Qualifications

• Bachelor's degree in a quantitative field (Statistics, Data Science, Mathematics, Computer Science, Economics, Engineering) or related discipline; Master’s a plus
• 1-2 years of relevant experience for Path A; fresh graduates with strong quantitative depth considered for Path B

Nice to Have: 

• Exposure to causal inference or incrementality measurement (difference-in-differences, synthetic control, uplift modeling) — a genuine plus if you have it, not required to apply
• Familiarity with modern data lakehouse/lakebase (Databricks/GCP experience a plus)
• Experience with data visualization tools (Tableau, Metabase preferred)