Data Scientist

Unchain Data; Kuala Lumpur; On-site; MYR 90,000 - 150,000; Full time

Job summary

MetaComp Pte Ltd is seeking a hands-on Data Scientist (BI & Applied Analytics) to turn complex business and transaction data into trusted insights, dashboards, and analytical solutions. You will work across payments, digital assets, finance, operations, risk, and compliance, combining business intelligence with statistical and machine-learning techniques to support better decisions.

You will build and maintain BI dashboards, define metrics, and develop models for forecasting and risk scoring,

Qualifications

• Bachelor's or master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or related field.
• At least 3 years of experience in data science, business intelligence, or advanced analytics.
• Strong proficiency in SQL and Python.
• Hands-on experience with Power BI, Tableau, Looker, Metabase, or similar BI platforms.

Responsibilities

• Translate business questions into KPIs, dashboards, analytical models, and actionable recommendations.
• Build and maintain BI dashboards for management, Finance, Product, Operations, Risk, and Compliance.
• Define standardized metrics, semantic models, and reporting logic for consistent business reporting.
• Analyze customer, transaction, revenue, operational, and external data to identify trends, risks, and opportunities.
• Develop forecasting, anomaly-detection, fraud, risk-scoring, and customer-segmentation models.
• Design data marts and analytical datasets with Data Engineers.
• Automate recurring reports and enable governed self-service analytics.
• Validate data accuracy and reconcile BI outputs with systems.
• Monitor dashboard usage, data freshness, model performance, and reporting quality.
• Present findings clearly to management and stakeholders.
• Maintain documentation for KPIs, reports, analytical methods, and data definitions.

Skills

SQL

Python

BI tools

Executive dashboards

KPI design

Statistics

Data modelling

Stakeholder comms

English & Mandarin

Education

Bachelor's or Master's in Data Science/Statistics/Math/CS/Economics

Tools

Power BI

Tableau

Looker

Metabase

Spark

Airflow

dbt

MLflow

Job description

About Us

MetaComp Pte Ltd is a leading Singapore-based digital payment solution provider, licensed and regulated by the Monetary Authority of Singapore (MAS) as a Major Payment Institution, to provide Digital Payment Token Services and Cross-border Payment Transfers. Operating under a P2B2C (platform-to-business, partners-to-clients) model, MetaComp provides its clients with an integrated end-to-end suite of services, empowering them to confidently enter the digital asset market with much-needed safety, security, and compliance assurance. Together with its parent company, Metaverse Green Exchange Pte. Ltd. (a MAS-licensed CMS holder permitted to carry out, inter alia, brokerage and custody services), MetaComp introduces its suite of services through CAMP (Client Assets Management Platform) which allow businesses to develop and scale their digital asset offerings through various products and/or services such as over-the-counter transactions, fiat payments, digital asset custody and prime brokerage.

The Role

We are looking for a hands-on Data Scientist (Business Intelligence & Applied Analytics) to turn complex business and transaction data into trusted insights, dashboards, and analytical solutions. You will work across payments, digital assets, finance, operations, risk, and compliance, combining business intelligence with statistical and machine-learning techniques to support better decisions.

Responsibilities

• Translate business questions into KPIs, dashboards, analytical models, and actionable recommendations.
• Build and maintain BI dashboards for management, Finance, Product, Operations, Risk, and Compliance.
• Define standardized metrics, semantic models, and reporting logic to ensure consistent business reporting.
• Analyze customer, transaction, revenue, operational, and external data to identify trends, risks, and opportunities.
• Develop forecasting, anomaly-detection, fraud, risk-scoring, and customer-segmentation models.
• Design data marts and analytical datasets with Data Engineers.
• Automate recurring reports and enable governed self-service analytics.
• Validate data accuracy and reconcile BI outputs with operational and financial systems.
• Monitor dashboard usage, data freshness, model performance, and reporting quality.
• Present findings clearly to management and business stakeholders.
• Maintain documentation for KPIs, reports, analytical methods, and data definitions.

Requirements

• Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
• At least 3 years of experience in data science, business intelligence, or advanced analytics.
• Strong proficiency in SQL and Python.
• Hands‑on experience with Power BI, Tableau, Looker, Metabase, or similar BI platforms.
• Experience building executive dashboards, operational reports, and reusable analytical datasets.
• Good understanding of KPI design, dimensional modelling, semantic layers, and data visualization.
• Solid knowledge of statistics, forecasting, experimentation, and machine learning.
• Experience working with large structured and semi-structured datasets.
• Ability to translate business requirements into measurable analytical solutions.
• Strong business acumen, problem-solving skills, and stakeholder communication.
• Professional proficiency in English and Mandarin for collaboration with Chinese‑speaking vendors and technical teams.

Nice to Have

• Experience in fintech, payments, banking, blockchain, or digital assets.
• Knowledge of financial reconciliation, revenue analytics, AML, fraud, transaction monitoring, or regulatory reporting.
• Experience with Power BI semantic models, DAX, data marts, and row‑level security.
• Experience with forecasting, anomaly detection, customer segmentation, or graph analytics.
• Familiarity with Spark, Airflow, dbt, MLflow, or cloud data platforms.
• Experience with generative AI, natural-language BI, or AI‑assisted analytics.
• Understanding of data governance, model governance, privacy, and regulated environments.