Top Analyst Jobs in Bangalore

Perform advanced data analysis, visualization, and business intelligence work for clients across industries. Translate business problems into analytical structures, apply statistical and machine learning techniques, map business processes, generate data outputs, interpret quantitative results, and collaborate with data science and engineering teams. The role also manages data analysts, supports client engagements, and helps embed analytics and AI into business decision-making.

Cleanses and maintains master data across materials, customers, vendors, and finance. Performs data profiling, validation, quality analysis, root-cause investigation, dashboard development, KPI reporting, and governance activities. Collaborates with business, MDM, and data governance teams to enforce data standards, document metadata, resolve issues, and provide actionable insights to stakeholders.

Leads enterprise MDM and PIM implementations by facilitating discovery, documenting requirements, designing data governance and migration strategies, configuring platforms, and managing UAT. Profiles legacy data, defines mappings and quality rules, maintains traceability, coordinates stakeholders and vendors, manages scope and defects, creates documentation, and trains client teams. The role requires rapidly mastering MDM platforms, using AI tools responsibly, and translating technical constraints into business terms.

Analyze and model data from multiple sources, build reliable datasets and dashboards, validate data quality, conduct statistical analyses and experiments, and translate findings into business recommendations. Partner with cross-functional stakeholders across marketing, operations, finance, and product. Promote data literacy, document best practices, and support data-driven decision-making. The role requires strong SQL, Python or PySpark, BI tools, Databricks, financial services knowledge, and experience with credit risk, lending, governance, and customer lifecycle analytics.

Supports AI initiative delivery by identifying business opportunities, gathering requirements, translating needs into technical specifications, assessing business value, and coordinating stakeholders, data scientists, engineers, IT teams, and vendors. The role also supports Azure AI solution delivery, data governance, ethical AI compliance, change management, user adoption, documentation, and process optimization.

Leads complex analytics initiatives, translates business needs into scalable data solutions, develops KPI frameworks, and delivers actionable insights through SQL, Python or R, dashboards, and reporting. Partners with senior stakeholders on analytical roadmaps, mentors junior team members, and supports data-driven decision-making. Responsibilities include data extraction, manipulation, automation, statistical modeling, data visualization, performance tracking, and business reporting.

Develop and execute marketing analytics strategies, oversee Python-based ETL pipelines and SQL data environments, maintain Tableau and Adobe Analytics reporting solutions, establish data governance and quality standards, define KPIs, deliver actionable insights, manage analytics projects, and present findings to leadership.

Analyzes, cleans, validates, and interprets data from multiple sources to generate actionable business insights. Uses Python or R, SQL, Excel, and Power BI or Tableau to perform analysis, automate processes, and create dashboards and reports. Identifies trends and KPIs, ensures data accuracy, communicates findings, and collaborates with cross-functional stakeholders to support data-driven decisions.

Supports the enterprise data systems ecosystem by monitoring performance, managing system changes, troubleshooting incidents, resolving data and integration issues, administering access controls, maintaining documentation, and optimizing workflows through SQL, reporting, ETL, and automation tools. The role partners with business and technical teams on implementations, testing, upgrades, training, and continuous improvement.

Analyze business data, build and maintain business models, provide actionable insights and reports, collaborate with cross-functional teams, monitor performance, and recommend efficiency improvements to support strategic decision-making.

Leads end-to-end analytics for content-flow operations, translating business questions into hypotheses, KPI frameworks, dashboards, and actionable insights. Analyzes throughput, cycle times, quality, rework, supplier performance, workload, and operational bottlenecks using SQL and advanced analytical methods. Partners with senior stakeholders, data management, IT, and operations teams to improve data quality, governance, reporting adoption, and decision-making. Coaches junior analysts and leads tactical analytics projects.

Analyze existing data structures, map to new designs, write user stories and acceptance criteria, document data mappings/transformations, gather requirements, support developers and testers, and run workshops to ensure business-focused delivery.

Leads AI-driven reporting, analytics, and digital initiatives across the full project lifecycle. Designs dashboards, data architectures, ETL/ELT pipelines, APIs, and business intelligence solutions using cloud and AI technologies. Partners with stakeholders to define requirements, prioritize projects, manage delivery, and communicate technical concepts. Evaluates emerging tools, integrates agentic AI into reporting workflows, and drives continuous improvement, adoption, and measurable business value.

Lead MDM data consumption and validation across Customer 360/Reference 360. Validate data flows from MDM to APIs, batch pipelines and Snowflake; run SQL-based reconciliations; support UAT, defect tracking, requirements documentation, and downstream financial reporting validation. Act as analyst bridging producers and consumers, focusing on data quality and documentation rather than development.

Lead data analytics initiatives by developing Tableau and Looker dashboards, integrating and validating data from multiple sources, optimizing reporting performance, writing SQL and Python-based analyses, translating stakeholder needs into scalable solutions, and mentoring analysts. The role also supports data engineering, ETL/ELT processes, GCP applications, and continuous improvement of analytics practices.

Develop and maintain Power BI dashboards, reports, data models, measures, and DAX calculations. Extract and analyze data using SQL, validate report accuracy, troubleshoot data issues, and translate stakeholder requirements into actionable visualizations and insights. The role also involves documenting dashboard logic and data sources while collaborating with business stakeholders.

Develop and maintain Power BI dashboards and reporting solutions, write and optimize SQL queries, build data models and DAX calculations, validate data quality, and translate business requirements into actionable insights. The role involves stakeholder collaboration, troubleshooting reporting issues, documenting dashboard logic and data sources, and ensuring accurate, consistent reporting.

Evaluates AI outputs and workflows through human labeling, failure-mode analysis, benchmark maintenance, and quality reporting. The role maintains labeled datasets, golden sets, and regression slices; calibrates human graders; validates LLM-as-a-judge results; and identifies hallucinations, retrieval, tool-use, grounding, and workflow issues. It partners with Engineering, Product, QA, and evaluation teams to improve rubrics, assess product changes, monitor quality, and support release-readiness decisions.

Produce executive-grade dashboards and reports (Power BI, SSRS), analyze healthcare revenue cycle and financial/operational performance, identify root causes and trends, validate data across sources, and provide data-driven recommendations to Client Services and executive leadership to improve revenue and client outcomes.

Leads global people analytics, HCM reporting, and U.S. compliance reporting using Workday and PeopleSoft. Develops reporting solutions, gathers requirements, manages testing, troubleshoots integrations and workflows, maintains data mappings, and supports data audits. Partners with HR stakeholders on projects, ad hoc requests, privacy reviews, documentation, and training. Oversees reports including EEO, AAP, VETS-4212, California pay data, and other regulatory submissions while improving enterprise reporting processes.

Monitor and triage enterprise data pipeline incidents, investigate root causes, assess downstream impact, and coordinate escalations through resolution. Administer the Pantomath data observability platform, configure monitors and alerts, onboard pipelines, maintain integrations, and reduce alert noise. Communicate outage status and resolution timelines to stakeholders, document incidents and RCAs, support post-incident reviews, and conduct shift handoffs within a shift-based operations model.

As a Senior Business Systems Analyst, you will define system goals, capture business requirements, and work with engineering teams on SFDC implementations.

Develops dynamic client-facing reports and visualizations for investment services clients using IRD, MCD, and BI platforms. Analyzes large datasets, supports data modeling and data mart design, applies SQL for validation and optimization, and collaborates with data and product teams to ensure data integrity. Serves as an IRD subject matter expert while supporting reporting issues and complex global requirements across custody, digital, and fund services.

Develop digital analytics insights, metrics, and business intelligence to improve customer journeys, engagement, conversion, personalization, and digital experiences. Advise stakeholders on data strategy, optimize campaigns, manage analytics and data platforms, translate requirements into measurement solutions, and collaborate with tagging developers. Provide training, coaching, and senior-level guidance while influencing business decisions through data-driven recommendations.

Analyze business and product data, build data models, and maintain dashboards and reporting layers in Looker and Snowflake. Translate stakeholder questions into actionable insights, optimize SQL queries, and ensure metric consistency. Build AI-powered analytics tools and automations, support self-service data access, and communicate findings through reports and presentations. Lead analytics projects, collaborate cross-functionally, and coach junior team members.