Job Overview

Citi is hiring a Business Analytics Analyst - Operations for a hybrid full-time opportunity in Haryana, India. This role sits within the Operations Analytics function and focuses on using data to understand business performance, identify operational opportunities, and support better decision-making.

The position is suited to a developing analytics professional who can examine operational information, recognize meaningful patterns, and turn findings into practical recommendations. The work may cover areas such as customer experience, contact center performance, process efficiency, complaint analysis, capacity planning, staffing, card operations, and KYC-related activities.

The analyst will work with cross-functional stakeholders and business partners to gather information, evaluate processes, communicate insights, and support improvements. The role also provides exposure to automation, data visualization, programming, and analytical approaches used in financial services operations.

Key Responsibilities

• Gather operational and business data from multiple stakeholders and review historical performance.
• Analyze datasets to identify trends, inconsistencies, patterns, and opportunities for process improvement.
• Convert analytical findings into clear business insights and recommendations for planning and operational decisions.
• Support exploratory and confirmatory data analysis as well as qualitative analysis when required.
• Study customer and consumer behavior to support segmentation, targeting, complaint analysis, and customer experience improvements.
• Work with internal and external business partners to develop, implement, monitor, and improve decision strategies.
• Evaluate new data sources, analytical tools, and capabilities that can improve existing processes.
• Contribute to automation initiatives designed to make operational workflows more efficient.
• Present analytical findings clearly to business stakeholders and senior leaders.
• Consider operational and regulatory risks when supporting business decisions and follow applicable policies, controls, laws, and regulations.
• Escalate and report control concerns transparently when necessary.

Required Skills

A strong foundation in data analysis is important for this Business Analytics Analyst role. Candidates should understand statistical analysis, data mining, process mapping, and process improvement concepts. The ability to investigate data carefully and identify useful business patterns is essential.

Programming and data manipulation skills are also relevant. The position identifies Python and SQL as useful programming technologies, while automation exposure such as SAS and PySpark can support the development of analytical or operational solutions.

Candidates should be comfortable working with data visualization tools such as Tableau or QlikView. The ability to explain what a visualization means, rather than simply creating charts, is particularly valuable because the role requires translating data into recommendations.

Strong problem-solving ability is expected. The analyst should be able to examine an operational problem, determine what the available data indicates, consider business context, and communicate a practical conclusion.

Preferred Skills

Knowledge of banking or financial services operations is beneficial. Familiarity with regulatory areas such as KYC and AML can help candidates understand the business environment in which operational analytics decisions are made.

Exposure to Lean or Six Sigma methods, process re-engineering, customer feedback analysis, sentiment analysis, automation, and operational performance measurement can further strengthen an application.

Experience with tools such as SAS, PySpark, Python, SQL, Tableau, or QlikView should be described accurately on the resume. Candidates should explain the type of analysis or project completed rather than listing technologies without context.

Education

A Bachelor's or university degree is required, or equivalent experience. Candidates from analytical, business, technology, engineering, statistics, economics, computer science, or related educational backgrounds may be able to demonstrate relevant preparation through coursework and practical projects, provided their background aligns with the role requirements.

Experience

The job listing does not specify a fixed minimum or maximum number of years of experience. It describes the Business Analytics Analyst as a developing professional role with responsibility focused on the quality and impact of work delivered within the team.

Applicants should emphasize relevant experience from analytics projects, internships, academic work, business analysis assignments, process improvement initiatives, or professional roles where they used data to solve operational problems.

Required Technologies

Relevant analytical technologies and tools mentioned for the role include Python, SQL, SAS, PySpark, Tableau, and QlikView. The position also involves statistical analysis, data mining, data visualization, process mapping, process re-engineering, and automation.

These technologies should be viewed in the context of business analytics rather than software development alone. The key objective is to use data and technology to understand operational performance and support informed business decisions.

Soft Skills

Clear communication is important because the analyst must explain findings to business partners and senior leaders. The ability to simplify technical or analytical information for non-technical audiences can make recommendations more useful.

Attention to detail is also essential when working with operational data, identifying inconsistencies, and assessing results. Curiosity, structured thinking, collaboration, and practical problem-solving will help when investigating unfamiliar business questions.

A strong customer focus is valuable because the Operations Analytics team works on areas such as complaints, sentiment, contact center performance, and customer experience. Ethical judgment and awareness of risk are also important in a financial services environment.

Benefits of Working in this Role

This role can provide practical exposure to business analytics within a global financial services environment. Candidates can develop experience in data analysis, visualization, automation, process improvement, customer insights, and operational decision support.

The position can also help professionals understand how analytical findings are used by business teams to improve processes, manage performance, and support customer-focused initiatives. Exposure to KYC, AML, operational controls, and financial services practices can be valuable for candidates interested in banking analytics.

Work Mode

The role is listed as Hybrid. The job listing identifies Haryana, India as the location and indicates a full-time schedule.

Location

The listed location is Haryana, India. The supplied job URL references Gurugram, Haryana, making Gurugram the likely city associated with the posting.

Who Should Apply

This opportunity is suitable for candidates interested in business analytics, operations analytics, data analysis, process improvement, customer insights, and financial services. Applicants should be comfortable working with structured data and communicating analytical conclusions.

Candidates with knowledge of Python, SQL, Tableau, QlikView, SAS, or PySpark should highlight relevant projects and measurable outcomes. Those with banking, KYC, AML, customer operations, Lean, Six Sigma, or process improvement exposure can also emphasize those areas.

Career Growth

Experience in operations analytics can create a foundation for future roles in business analytics, decision management, data analytics, process improvement, customer analytics, automation, and financial services strategy. Over time, professionals can deepen their technical analytics skills while building stronger business and stakeholder management capabilities.

Application Advice

Customize your resume for the Business Analytics Analyst role. Lead with projects or experience that demonstrate data analysis, statistical reasoning, SQL or Python usage, dashboards, process improvement, automation, or customer insight generation.

Where possible, explain the business problem, the data used, the analysis performed, the tools applied, and the outcome. If you have worked with Tableau, QlikView, SAS, PySpark, KYC, AML, Lean, or Six Sigma, include those skills only where you have genuine exposure.

Also prepare to discuss how you would validate data, identify trends, communicate an analytical finding, and turn an insight into an operational recommendation. Because the role operates within financial services, demonstrate careful attention to controls, risk, compliance, and responsible decision-making.