Role Overview

We are looking for Financial Risk Modelling/Analytics and R Developers with a solid foundation in Financial Markets, Financial Risk Modelling and Analytics, combined with excellent programming skills in R and SQL/KQL.

The role involves developing financial-services applications and analytical solutions for Hedge Funds, Wealth Management firms, Asset Managers, and Corporate Treasury clients. Candidates will work across the data and application lifecycle, including data ingestion, ETL, risk analytics, financial modelling, exploratory data analysis, scenario analysis, workflow development, testing, and cloud-based application development.

R programming will be the primary development language for this role. Candidates should be comfortable using R not only for statistical analysis, but also for developing reusable, maintainable analytical components and application workflows.

A strong understanding of Financial Risk Analytics, Statistics/Econometrics, Data Structures, and RDBMS concepts is required. Experience with Python, Azure Cloud Services, and BI tools will be an advantage.

This opportunity is particularly suited to fresh graduates and early-career developers with 0–2 years of experience who have strong analytical and programming skills and are interested in building a career in Financial Technology, Financial Markets, and Risk Analytics.

Key Responsibilities

- Develop and maintain Financial Markets and Risk Analytics applications using R and related Microsoft data technologies.
- Implement financial risk analytics, modelling, statistical analysis, and scenario-based analysis.
- Perform exploratory data analysis (EDA), data validation, reconciliation, and local analysis/debugging using tools such as R, SQL, and Excel.
- Build data-ingestion and ETL workflows for structured and unstructured financial data from multiple sources.
- Develop and test workflows and data pipelines, including integration with databases and external APIs.
- Work with SQL/KQL databases and RDBMS systems for data retrieval, transformation, validation, and analysis.
- Develop reusable R functions, modules, and analytical components suitable for production applications.
- Troubleshoot and debug data, code, analytical calculations, and workflow-related issues.
- Work with financial-market data and understand how data flows through an end-to-end risk analytics application.
- Collaborate with developers, analysts, and domain experts to translate financial and business requirements into robust technical solutions.

Mandatory Skills - R Programming & Analytics

- Strong hands-on programming experience in R.
- Strong understanding of R programming concepts, including:




- R libraries/packages
- User-defined functions
- Object-oriented programming concepts
- Loops and iterative processing
- Regular expressions
- Exception/error handling
- Logging
- Debugging and troubleshooting
- Data manipulation and transformation
- Solid foundation in Statistics and/or Econometrics.
- Strong analytical, quantitative, and problem-solving skills.

Financial Markets & Risk

- Strong understanding of Financial Markets and Financial Risk Analytics.
- Understanding of financial risk data, risk metrics, modelling concepts, and analytical workflows.
- Ability to perform scenario analysis and exploratory analysis of financial and risk data.
- Exposure to areas such as Market Risk, Credit Risk, P&L;/Risk Analytics, VaR, Stress Testing, or related financial risk concepts is desirable.

Database & Data Engineering

- Strong understanding of RDBMS concepts.
- Strong hands-on knowledge of SQL and/or KQL, including writing and troubleshooting queries.
- Ability to access and query databases both through database/query interfaces and programmatically using R.
- Understanding of ETL/data-ingestion processes and data-quality validation.
- Ability to work with data from multiple sources and formats.

Data Extraction & Integration

- Experience or strong understanding of working with APIs, including REST APIs.
- Ability to consume, process, validate, and integrate API-based data using R.
- Experience handling JSON, XML, HTML, PDF, and other structured/semi-structured data.
- Knowledge of data extraction, web scraping, text mining, and data manipulation will be an advantage.

EDA, Excel & Local Analysis

- Good working knowledge of Excel for exploratory data analysis, local debugging, reconciliation, and scenario analysis.
- Ability to independently investigate data and analytical discrepancies using R, SQL, and Excel.
- Ability to validate analytical outputs and investigate unexpected results through structured analysis.

Desired Skills

- Fundamentals of Python and experience using Python for data processing or analytics.
- Knowledge of Azure Cloud Services, particularly Azure-based data and application development.
- Experience with BI/visualization tools.
- Fundamentals of AI/ML concepts.




- Familiarity with API testing tools and development/debugging utilities.
- Exposure to financial technology, quantitative analytics, or financial-services applications.

Candidate Profile

- 0–2 years of overall experience; fresh graduates are encouraged to apply.
- Strong academic foundation in Statistics, Economics, Econometrics, Data Science, or closely related quantitative disciplines.
- Strong analytical thinking, quantitative reasoning, and programming ability.
- Candidates with academic, internship, or personal projects involving R, financial analytics, risk modelling, statistical analysis, or financial-market data are encouraged to showcase them during the interview.
- Candidates should be able to demonstrate 1–2 relevant projects involving data analytics, financial/risk modelling, R programming, or related areas.
- Strong debugging and troubleshooting ability.
- Good communication skills and ability to work effectively in a collaborative environment.
- Detail-oriented, self-motivated, and comfortable working in a fast-paced FinTech environment.

Minimum Qualification Bachelor's or Master's degree in Statistics, Economics, Econometrics, Data Science, or a closely related quantitative discipline.

About Financial Fabric

Financial Fabric (www.financialfabric.com) is a FinTech startup with registered offices in the United States and India, providing DataHub technology services to hedge funds, asset managers, wealth managers, institutional investors, broker-dealers, and other financial-services organizations.

The Financial Fabric DataHub service leverages Microsoft data platforms, proprietary data models, and analytics to address a range of financial data and analytical problems. The platform combines traditional data technologies with modern analytics and machine-learning capabilities.

As part of the Financial Fabric development team, you will have the opportunity to learn and contribute to the development and rollout of financial-services analytics solutions using modern cloud technologies, big-data platforms, and analytical frameworks.

We offer a fast-paced and challenging environment where developers work on new products and solutions for financial-services clients, with significant opportunities for learning, technical development, and professional growth.

Pay: ₹280,000.00 - ₹320,000.00 per year

Benefits

- Provident Fund
- Work from home

Education:
- Bachelor's (Required)

Experience:
- total work: 1 year (Preferred)
- R: 1 year (Required)
- Excel: 2 years (Required)
- SQL: 1 year (Required)
- KQL: 1 year (Preferred)

Location:
- Kolkata, West Bengal (Required)

Work Location: In person

📌 Financial Markets - Risk Analytics & Modelling with R Developer (Kolkata)
🏢 Financial Fabric
📍 Kolkata