Data Analyst

GoTymeX; Bengaluru; On-site; INR 500,000 - 800,000; Full time

Job summary

GoTymeX is seeking a Data Analyst to dig into numbers, build reliable datasets, and turn findings into practical recommendations. You will partner with teams across the company to understand questions, explore data, and empower data-driven decisions.

Responsibilities include data exploration, modeling, dashboard development, and running experiments to evaluate initiatives. You will help strengthen data literacy and share best practices across the organization.

Qualifications

• 2+ years in financial services, fintech, or banking analytics.
• Experience building analytical datasets and reports.
• Ability to translate data insights into business actions.

Responsibilities

• Collect, clean, and analyze data from multiple sources.
• Build core analytical datasets and dashboards.
• Collaborate with stakeholders to derive actionable insights.
• Develop and maintain KPI tracking and reporting tooling.
• Share knowledge and promote data literacy across teams.

Skills

SQL queries

Python/PySpark

Statistics

Data visualization

Experiment design

Business storytelling

Education

Bachelor's in Mathematics/Statistics/Economics/CS

Tools

Looker

Tableau

Databricks

Job description

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.

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. Support data-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

• 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
• 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
• 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