Job Description

About Us

Do you want to be part of Thailand banking transformation? Data is the core of the new financial services era, and we are open for the opportunity to be part to drive this change at the core.

SCB DATAx is a new venture of the Siam Commercial Bank (SCB) holdings, a leading financial services and digital services holdings in Thailand and ASEAN.

As part of the transformation of SCB into a group of product and technology companies, under the SCBx brand, SCB DATAx is the technology company to centralize data and provides AI and data science services and products to the group.

With a leading-edge cloud native data & AI platform, our vision is to support the group to providing everyone in our region with the opportunity to prosper.

We work on forward-thinking challenges of centralizing, analyzing and sharing information. We collaborate with companies and experts in many different domains, embrace diversity and all that while having a good laugh and joy in work.

Responsibilities

Lead the translation of complex business requirements and use cases from internal and external stakeholders into scalable data products and analytics solutions that directly support strategic objectives.
Act as a trusted advisor to business leaders, proactively identifying opportunities where data can drive growth, efficiency, or risk mitigation.
Define and apply appropriate statistical methodologies, analytical frameworks, and measurement approaches, including identifying and integrating new or external data sources to enhance analytical depth.
Own the end-to-end transformation of business requirements into technical specifications and documentation (e.g., BRS, data contracts), ensuring clear alignment with BI Engineers, Data Scientists, and Data Engineers.
Lead and oversee Exploratory Data Analysis (EDA), including defining data requirements, assessing data quality, designing transformation logic, and establishing data cleansing and standardization rules aligned with enterprise data models.
Design and implement scalable data processing and analytical workflows using SQL, Python, and BI tools (e.g., Power BI) to generate insights, forecasts, and data-driven recommendations.
Drive data validation and quality assurance processes, working closely with engineering teams to ensure accuracy, consistency, and reliability of data outputs.
Oversee and support UAT processes, ensuring delivered solutions meet business requirements and are production-ready.
Establish and maintain metadata standards (business, technical, dataset-level) in alignment with Data Governance policies, ensuring data is well-documented, discoverable, and usable across the organization.
Identify and define Critical Data Elements (CDEs), and lead the design and review of data quality rules in collaboration with Data Quality teams.
Translate analytical findings into clear business implications and actionable recommendations, influencing decision-making at senior levels.
Communicate insights and proposals through executive-level storytelling and visualization, using tools such as PowerPoint and dashboards to drive alignment and action.
Take full ownership of project delivery, including scope definition, prioritization, stakeholder management, and timeline execution.
Provide mentorship, guidance, and quality oversight to junior analysts and team members, acting as a subject matter advisor and promoting best practices, analytical rigor, and continuous improvement within the team.
Independently troubleshoot complex data, logic, and stakeholder issues, proactively resolving ambiguities, managing competing priorities, and maintaining strong alignment across cross-functional stakeholders.

Qualifications

Bachelor’s or Master’s degree in a quantitative field (e.g., Business, Computer Science, Mathematics, Engineering, Economics, or Finance).
5–8+ years of experience in analytics, business intelligence, or data science, with a proven track record of delivering high-impact insights and solutions.(preferably in financial or banking sector)
Advanced proficiency in SQL for complex querying, data transformation, and performance optimization.
Strong experience with in advanced data wrangling, statistical analysis, and modeling.
Demonstrated expertise in analytics, data science, business intelligence (BI), and strategy development.
Strong understanding of data governance, data quality frameworks, and data modeling concepts.
Proven ability to translate data into strategic insights and effectively present to senior management and executives.
Excellent communication, stakeholder management, and interpersonal skills, with the ability to influence cross-functional teams.
Strong data-driven mindset, with experience in performance measurement, KPI design, and decision support.
Experience mentoring or leading analysts or project teams is highly preferred.