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Location
In office (Bengaluru)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 16, 2026. GoTymeX scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Founded in 2016, GoTymeX (formerly TymeX) is the global product, technology, and software development hub for digital banking enterprise Tyme Group. Headquartered in Ho Chi Minh City, Vietnam, the company specializes in engineering reusable, cloud-native banking platforms, microservices architectures, data analytics infrastructure, and AI-driven customer interaction systems. By building scalable financial software assets that can be rapidly deployed and localized across emerging markets - including South Africa and the Philippines - the organization enables digital retail banks to lower operating costs, accelerate feature rollouts, and scale multi-country banking services.

Description

About This Role:

We’re looking for a Data Analyst who’s excited to dig into the numbers, uncover insights, and help the business make smarter decisions. In this role, you’ll partner with teams across the company to understand their questions, explore the data, and turn your findings into clear, practical recommendations.

While your main focus will be analysis and storytelling, you’ll also bring solid technical skills to the table - helping us build reliable datasets, improve reporting, and make sure our data is accurate and easy to use. You’ll play a big part in strengthening our data-driven culture by making information more accessible and empowering colleagues to use data with confidence.

Requirements

Data Exploration & Modeling

  • Collect, clean, and analyze data from multiple sources to support business needs.
  • Build and maintain core analytical datasets and reports for cross-functional teams.
  • Ensure accuracy, consistency, and reliability of data through validation and quality checks.
  • Apply statistical and analytical techniques to uncover trends and opportunities.

Business Partnership & Strategic Analysis

  • Collaborate with business stakeholders to understand requirements and deliver actionable insights.
  • Conduct in-depth analyses on customer behavior, product usage, and market trends.
  • Translate complex data findings into clear, impactful recommendations for business strategy.
  • Supportdata-driven decision-making across marketing, operations, finance, and product teams.

Analytics

  • Develop dashboards and KPI tracking tools to monitor business performance.
  • Design and execute experiments (e.g., A/B tests) to evaluate initiatives.
  • Present insights clearly and compellingly to technical and non-technical audiences.

Team Development & Knowledge Sharing

  • Promote data literacy by helping colleagues understand and leverage analytical tools.
  • Share best practices in data analysis, visualization, and reporting.
  • Contribute to documentation and training to enhance organizational analytics maturity.
  • Dedicate a portion of time to cross-team projects that enhance company-wide data capabilities.

Requirements

1. Technical Skills

  • Programming: Strong SQL expertise including complex queries, CTEs, window functions, and optimization
  • Languages: Proficiency in Python or PySpark for data manipulation and analysis
  • Statistics: Solid foundation in statistical analysis, hypothesis testing, and experimental design
  • Data Visualization: Experience with BI tools (Looker preferred, Tableau, or similar)
  • Experience with Databricks

2. Business & Financial Services

  • 2+ years experience in financial services, fintech, or banking environment
  • Understanding of credit risk, lending products, and regulatory requirements
  • Knowledge of GDPR and data governance
  • Experience with customer lifecycle analytics and retention strategies

3. Core Competencies

  • Business Judgment: Ability to make strategic and operational decisions using data
  • Problem-Solving: Tackle complex problems involving business, regulatory, and operational variables
  • Communication: Exceptional ability to influence stakeholders and present data convincingly
  • Collaboration: Experience working cross-functionally with non-technical teams

*Preferred Qualifications

  • Bachelor's degree in Mathematics, Statistics, Economics, Computer Science, or related quantitative field
  • Experience with big data technologies and cloud platforms
  • Machine learning and AI knowledge
  • Previous experience in high-growth startup environments
  • Familiarity with data modeling using statistical algorithms
  • Experience building automated testing and monitoring systems
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