Lead Product Analyst

A day in your life might include (what you will be doing/ key responsibilities)

Key Responsibilities

1. Team Leadership & People Management• Manage a team of 4 Data Analysts of mixed seniority: set goals, allocate work across initiatives, and review output quality.

• Own hiring, onboarding, and performance management for the team, including regular 1:1s, feedback, and career development plans.

• Build team rituals, ways of working, and coding/analysis standards that scale as headcount grows.

2. Product Analytics Strategy & Roadmap• Define and prioritize the analytics roadmap across product verticals in partnership with Product leadership.

• Decide what the team should — and should not — spend time on, balancing ad-hoc stakeholder requests against strategic analysis.

• Establish the core metrics framework (business outcome, customer guardrail, and execution-quality tiers) for major product initiatives.

• Own the analytics tooling, event tracking, and data-quality agenda for the pod (data warehouse, dbt models, dashboards), in coordination with Data Engineering.

3. Actionable Insights & Stakeholder Management• Business and product fluency: Understand target customers, their needs and pain points; connect data insight to product strategy and contribute directly to roadmap planning.

• Insight delivery: Use data storytelling — not just reporting — to influence stakeholders and drive product decisions.

• Stakeholder alignment: Manage stakeholder expectations — set realistic timelines and proactively communicate challenges or roadblocks before they become escalations.

• Go-live / GTM: Work with Marketing, Sales, and Product to keep go-to-market activities aligned and effective; report on GTM performance to executive leadership.

4. Technical Oversight & Quality• Review and quality-check the team's analysis for rigor, especially for high-stakes or leadership-facing work.

• Stay hands-on enough to unblock the team on complex technical problems and to credibly evaluate their work.

• Set technical best practices and documentation standards across the pod, ensuring consistency as the team grows.

Must

Yêu cầu công việc

Must-Have

• Bachelor's degree in Statistics, Computer Science, Data Science, Economics, or another quantitative field; Master & MBA a plus.

• 6–8+ years of data analysis experience, including at least 2 years directly managing an analyst team (hiring, performance reviews, career development).

• Strong SQL and/or Python (pandas); comfortable reviewing others; technical work, not only producing your own.

• Track record of partnering with Product or Business leadership to shape an analytics agenda, not just execute requests.

• Demonstrated experience presenting to and influencing senior/executive stakeholders.

• Experience in fintech, banking, or a fast-scaling tech/e-commerce environment.

Nice-to-Have

• Experience building or scaling an analytics team or function from a smaller base.

• Familiarity with modern data warehousing and transformation tools (BigQuery, Redshift, Snowflake, dbt, etc.).

• Exposure to lending, payments, or digital banking data and regulatory context.

• Experience with product/CRM analytics platforms (Amplitude, MoEngage, AppsFlyer, Firebase, etc.).

Quyền lợi

• Thưởng: 13th-month salary Paid annual leave Dynamic, technology-friendly working environment with up-to-date processes Negotiable and competitive salary Healthcare insurance Government-mandated social, health, and unemployment insurance