About the Role:

Hudson Data Private Limited is looking for a highly analytical Business Data Analyst with strong hands-on experience in SQL, data analysis, financial services, risk and/or fraud analytics.

We are looking for candidates who can go beyond traditional requirement gathering and independently work with data to analyze input and output files, identify discrepancies, investigate anomalies, reconcile data, perform root-cause analysis, and translate findings into business and technical requirements.

The ideal candidate should have experience working with complex datasets in Banking, FinTech, Lending, Payments, Risk, Fraud or Financial Services environments.

Key Responsibilities

- Analyze large datasets using SQL and Excel to identify trends, anomalies, exceptions and data-quality issues.
- Perform input vs. output analysis and validate data across multiple systems.
- Reconcile source data with system-generated outputs and identify missing, duplicate or incorrectly processed records.
- Perform root-cause analysis (RCA) for data discrepancies and system/process issues.
- Analyze financial transactions, customer/account data, risk indicators and fraud-related patterns.
- Understand business rules and validate whether system outputs are being generated correctly.
- Translate business problems into functional requirements, business rules, user stories and acceptance criteria.
- Work closely with Business, Product, Operations, Data and Technology teams.
- Create test scenarios and perform UAT and data validation.
- Use SQL to independently validate system changes and production results.
- Identify process gaps and recommend data-driven improvements and controls.
- Develop reports, dashboards and exception monitoring using Power BI/Tableau/QuickSight or similar tools.
- Clearly communicate analytical findings and recommendations to business and technical stakeholders.

Must-Have Skills





- 6 to 10 years of relevant experience in Business Analysis / Data Analysis / Risk Analysis / Fraud Analysis.
- Strong hands-on SQL skills.
- Strong Excel skills, including PivotTables, XLOOKUP/VLOOKUP, SUMIFS/COUNTIFS and data reconciliation.
- Experience analyzing large datasets and input/output files.
- Strong experience in data reconciliation, exception analysis and root-cause analysis.
- Understanding of business rules and data-validation techniques.
- Experience with requirements gathering, user stories, acceptance criteria and UAT.
- Strong analytical and problem-solving skills.
- Good written and verbal communication skills.

Preferred Skills

- Experience in Banking, FinTech, Lending, Payments, Credit Risk, Fraud or Financial Services.
- Experience analyzing financial or transactional data.
- Power BI / Tableau / QuickSight, Google Looker
- Basic Python knowledge.
- Understanding of APIs, JSON, databases, ETL and data pipelines.
- Jira / Confluence experience.
- Exposure to AWS / Azure / GCP is an advantage.

What We Are Looking For We are looking for a candidate who can independently investigate:

Input Data Business Rules Processing Output Exception Root Cause Resolution The candidate should be comfortable answering questions such as:

- Why does the output not match the input?
- Which records are impacted?
- What patterns exist in the exceptions?
- Is the issue caused by source data, mapping, transformation or business logic?
- How can SQL be used to validate the issue?
- What change is required?




- How should the solution be tested?

This is not a purely documentation-based Business Analyst position. Strong hands-on data analysis and SQL capabilities are important for this role.

Preferred Candidate Background

Candidates currently working as any of the following are encouraged to apply:

Business Data Analyst | Business Analyst | Data Analyst | Risk Analyst | Fraud Analyst | Financial Data Analyst | Data Quality Analyst | Product Analyst

Candidates with experience in FinTech, Banking, NBFC, Lending, Payments, Credit Risk, Fraud Detection, Transaction Monitoring, Reconciliation or Financial Data Analysis will be preferred.

Why Join Hudson Data?

At Hudson Data, youll be part of a dynamic, innovative, and globally connected team that combines advanced AI/ML frameworks, modern data technologies, and cloud-based analytics platforms to solve complex, real-world business challenges. Youll have the chance to experiment with new approaches, deepen your technical expertise, and see your work translate into measurable business impact within a culture that values creativity, precision, collaboration, and continuous learning.

Our work spans high-impact domains including unsecured lending, BNPL, insurance, healthcare, and fraud analytics, where data science plays a critical role in solving commercially significant problems. Youll work on applications involving predictive modeling, risk scoring, fraud detection, customer and payment behavior, and decision intelligenceproviding the opportunity to apply advanced analytical techniques to problems where model quality directly influences business outcomes.

For Data Scientists interested in applied machine learning rather than purely theoretical modeling, Hudson Data offers the opportunity to work at the intersection of advanced analytics, domain expertise, and real-world decision-making.

📌 Business Analyst Finance, Risk & Fraud (Gurugram)
🏢 Hudson Data
📍 Gurugram