Data Analyst (Logistics/Supply Chain Platform)

DADACONSULTANTS PTE. LTD.; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

DADACONSULTANTS PTE. LTD. is seeking a Data Analyst (Risk Control & Large-Truck Business Analyst) to perform risk analytics, FT L business analysis, and governance across multi-market operations.

The role emphasizes building metrics, evaluating strategies, and collaborating with Risk Strategy, Algorithm, Product, and Operations teams to drive measurable improvements.

Qualifications

• Bachelor's degree or above in Statistics, Mathematics, Computer Science, Economics or related discipline.
• At least 2 years of data analytics experience in internet platforms, logistics, or fintech helpful.
• Strong proficiency in SQL and Python for data processing and analysis.
• Experience with big data platforms is preferred.

Responsibilities

• Risk Control Analytics: analyze platform risk scenarios, identify indicators and patterns, evaluate rule effectiveness.
• Large-Truck Business Analytics: evaluate FT L transportation performance and pricing strategies.
• Metrics & Monitoring: build dashboards and monitoring frameworks across markets.
• Experimentation & Impact Evaluation: design evaluation methodologies, run A/B tests and causal inference.
• Cross-Functional Collaboration: work with Risk Strategy, Algorith m, Product, Ops and Eng teams to implement findings.

Skills

SQL

Python

Statistics basics

Experimental design

Data analytics

Education

Bachelor's degree or above

Tools

MaxCompute

Hive

Spark

Job description

Data Analyst (Risk Control & Large-Truck Business Analyst)

Key Responsibilities

1. Risk Control Analytics: Conduct data analysis across platform risk management scenarios, including fake transactions, order manipulation, promotional abuse, organised fraud and operational violations. Identify risk indicators and fraudulent patterns, evaluate risk control strategy effectiveness using metrics such as interception rate, precision, false-positive rate and financial losses, and drive continuous improvements to rules and models.

2. Large-Truck Business Analytics: Analyse the business performance and strategies of the full-truckload (FTL) transportation business. Identify opportunities and issues across cargo supply, transportation capacity, truck-to-cargo matching efficiency, fulfilment quality and pricing, and develop actionable recommendations to improve business strategies and products.

3. Metrics & Monitoring: Build core metrics frameworks and monitoring dashboards covering risk control and large-truck operations across multiple markets. Identify anomalies, investigate root causes and establish reusable analytical frameworks.

4. Experimentation & Impact Evaluation: Design and implement evaluation methodologies for risk control, operational and product strategies, including A/B testing, phased rollouts and causal inference. Quantify the benefits and costs of different strategies to improve decision-making efficiency and the reliability of analytical conclusions.

5. Cross-Functional Collaboration: Work closely with Risk Strategy, Algorithm, Product, Operations and Engineering teams, including teams at China headquarters and in other markets, to implement analytical findings and track business impact.

Requirements

1. Bachelor's degree or above in Statistics, Mathematics, Computer Science, Economics or a related discipline.

2. At least 2 years of data analytics experience. Experience in internet platforms, transaction-matching businesses, logistics or financial technology is preferred. Experience in risk control or fraud analytics is an advantage.

3. Strong proficiency in SQL and Python for data processing and analysis, with a good understanding of statistical methods and experimental design. Experience with big data platforms such as MaxCompute, Hive or Spark is preferred.

4. Strong business acumen and problem-solving skills, with the ability to break down complex problems, formulate hypotheses, validate them using data and translate insights into actionable recommendations.

5. Strong attention to data anomalies and the ability to identify suspicious patterns through user behaviour, transaction flows and relationship networks.

Regret to inform that only shortlisted candidates will be notified.