Business Intelligence Lead

DUOTECH PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

DUOTECH PTE. LTD. is seeking a highly analytical BI Lead to join our global BI & strategy team.

You will translate complex datasets into actionable business strategies, detect abnormalities, and deliver executive-ready insights for leaders and clients. You will develop automated data pipelines and dashboards using SQL and Python, perform root-cause analyses, and collaborate with data engineering and business units to align analytical solutions with real-world needs.

Qualifications

• Bachelor's or Master's degree in a quantitative field such as CS, statistics, data science, or finance.
• Expert SQL with ability to query large databases and optimize performance.
• Strong Python coding for data manipulation (Pandas, NumPy) and automated analysis.
• 5+ years in data analysis, identifying business trends and solving real problems.
• Ability to tell a data story and explain the why and so what clearly.
• Fluency in English and Mandarin to work with global teams.
• Fintech experience and knowledge of financial data structures is desirable.

Responsibilities

• Deep-dive into customer behavior, business performance, and metrics to identify growth opportunities and risks.
• Identify data abnormalities and perform root cause analysis to clarify findings for stakeholders.
• Develop and optimize automated data pipelines and dashboards for real-time reporting.
• Translate technical findings into concise executive summaries and insights for leaders.
• Collaborate with data engineering and business units to align analytical solutions with business needs.

Skills

Advanced SQL

Data analysis

Storytelling with data

English & Mandarin

Root cause analysis

Education

Bachelor's or Master's in quantitative field

Tools

Python

Pandas

NumPy

Job description

Job Description

We are looking for a highly analytical and business-savvy BI Lead to join our global business intelligence & strategy team. The ideal candidate is a master of data manipulation who can translate complex datasets into clear, actionable business strategies. You will be responsible for detecting business abnormalities, performing deep-dive root cause analysis, and delivering high-level summaries that guide our internal leaders and global clients.

Key Responsibilities:

Business Intelligence & Analysis: Deep-dive into customer behavior, business performance, and operational metrics to identify growth opportunities and potential risks.

Root Cause Investigation: Proactively identify data abnormalities (e.g., performance dips, operational shifts) and perform comprehensive root cause analysis to provide clarity to stakeholders.

Technical Execution: Develop and optimize automated data pipelines and dashboards using SQL and Python to ensure high-quality, real-time reporting.

Synthesis & Communication: Translate complex technical findings into concise executive summaries and natural language insights for non-technical business leaders.

Strategic Collaboration: Act as a bridge between data engineering and business units to ensure analytical solutions are perfectly aligned with real-world business needs.

Qualifications:

Educational Background: Bachelor's or Master's degree in a quantitative field (e.g., Computer Science, Statistics, Data Science, or Finance).

Technical Mastery: * Expert SQL: Proven ability to query large, complex databases and optimize performance.

Proficient Python: Strong coding skills for data manipulation (Pandas, NumPy) and automated analysis.

Business Analysis Experience: 5+ years of experience in data analysis, specifically in identifying business trends and solving real-world problems.

Synthesizing Ability: Exceptional ability to "tell a story" with data, moving beyond the "what" to explain the "why" and "so what" in clear business terms.

Communication: Fluency in English and Mandarin to effectively partner with our diverse global teams and stakeholders.

Industry Context: Direct experience in Fintech is highly desirable, with familiarity in financial data structures.