Data Scientist - Data Quality, Mining & Governance

OX Human Resources Consultancies; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

OX Human Resources Consultancies is seeking a Data Scientist to transform fragmented business data into reliable datasets and actionable insights. The role spans CRM, trading platforms, payment systems, KYC, and customer service data sources, focusing on data accuracy before analysis.

The successful candidate will apply data mining, statistical techniques, and client segmentation to identify patterns, risks, opportunities, and operational improvements across multiple internal systems.

Qualifications

• Experience cleaning, transforming and validating data from multiple sources.
• Strong SQL and Python skills for data processing and modelling.
• Ability to build data-driven insights for business decisions.

Responsibilities

• Data Cleaning & Data Quality: cleanse, standardise and reconcile large datasets from multiple internal systems.
• Data Mining & Business Analysis: identify patterns, trends, and opportunities; segment clients by behaviour and activity.
• Trading & Brokerage Data Analysis: analyse registration, deposits/withdrawals, trading activity and P&L.
• Statistical Modelling & Advanced Analytics: develop models to support churn, value, profitability and lifecycle.
• Data Definition & Governance: document rules, definitions, and data lineage with cross-functional teams.
• Reporting & Decision Support: translate analysis into clear recommendations and support BI teams.

Skills

Data cleaning

Data quality management

Data mining

Statistical analysis

Business insight generation

SQL

Python

Power BI

Tableau

Tools

Power BI

Tableau

Job description

OX Human Resources Consultancies is seeking a Data Scientist to transform fragmented business data into reliable datasets and actionable insights. The role spans CRM, trading platforms, payment systems, KYC, and customer service data sources, focusing on data accuracy before analysis.

The successful candidate will apply data mining, statistical techniques, and client segmentation to identify patterns, risks, opportunities, and operational improvements across multiple internal systems.