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Salary
≈ $8.5k – $21k per year (Estimated)
Location
In office (Ahmedabad)
Seniority
Junior · 2+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 4, 2026. First seen by Alion on Sep 29, 2026.

Overview
Company
Impact
Profile match
Trellance is a leading provider of business analytics for financial institutions, helping credit unions and banks meet the financial needs of digital consumers by delivering end-to-end products and solutions.

Company Detail

CU Rise Analytics Pvt. Ltd. is a wholly owned subsidiary of Trellance, Inc. CU Rise Analytics is an offshore development centre of Trellance Inc., working collaboratively to offer comprehensive solutions for data analytics, technology and talent to allow our credit union clients to provide high quality service to their members and remain competitive. Our core expertise lies in data science and technology, encompassing data analytics, predictive modelling, business intelligence, and technology services.

Trellance Cooperative Holdings, Inc. is a credit union cooperative and leading technology partner for credit unions. Its companies - consisting of Rise Analytics, ProBridge, Optiri and CUDX - provide innovative technology solutions for credit unions to increase efficiency, manage risk and improve the member experience. Trellance’s mission is to make sure credit unions have access to the tools and resources they need to grow, enhance member value and remain competitive in a rapidly evolving financial landscape.

Summary:

As a Data Analyst at Trellance, you will play an essential role in supporting financial institutions by analysing data, creating reports, and developing dashboards and visualizations to provide actionable insights. You will work closely with senior analysts and other stakeholders to contribute to the success of credit unions through data-driven decisions. This is an excellent opportunity if you’re looking to kickstart your career in data analysis, especially within the financial sector.

Key Responsibilities:

Data Extraction and Cleaning:

  • Extract and consolidate data from various sources, (Snowflake, SQL, or similar databases), spreadsheets, and external APIs.
  • Clean and preprocess data to ensure accuracy and consistency.

Data Analysis:

  • Analyse credit union data to identify growth, trends, patterns, anomalies, and actionable insights suitable for management and specific departments (like Finance, Marketing, Retail, Operations and Lending)
  • Perform statistical analysis to draw actionable insights.
  • Data sourcing and transformation of unstructured data into insightful data for reporting and project needs

Dashboard Development & Reporting:

  • Develop and create interactive and visually appealing dashboards using PowerBI or Tableau.
  • Customize dashboards to analyse business insights to meet the specific reporting needs of credit union management.
  • Create and maintain interactive dashboards and versioning using PowerBI or Tableau to visualize data and KPIs.
  • Generate regular and ad-hoc dashboard to track key performance indicators (KPIs) related to financial, marketing, operations, lending, and membership metrics.
  • Present findings to credit union management in a clear and understandable manner.

Python Coding (Optional):

  • Write and maintain Python code for data analysis, automation, and scripting tasks.
  • Develop and maintain data pipelines for efficient data processing.

Qualifications:

  • Bachelor’s degree in computer science, Statistics, Finance, Business, or a related field.
  • Data Analyst experience of 2-3 years, preferably with financial institution
  • Knowledge of SQL programming and database management.
  • Knowledge of data visualization tools like PowerBI or Tableau.
  • Strong analytical and problem-solving skills.
  • Good communication skills with the ability to work independently and as part of a team.
  • Attention to detail and a willingness to learn.

Skills Required:

Must-Have:

  • SQL
  • PowerBI or Tableau

Preferred / Nice to have:

  • Statistics
  • Python
  • Data warehousing concepts
  • Snowflake (or equivalent) knowledge
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