Top Analyst Jobs in Bengaluru

Monitor and investigate transaction data to detect fraud, build dashboards and models to track risk, refine detection rules and ML models, conduct root-cause analyses, and collaborate with data engineering, product, and compliance to improve fraud prevention.

The Business Analyst will analyze organizational information needs, design computer programs, recommend system modifications, and maintain user documentation while ensuring project milestones are met.

The Data Analyst will manage and analyze large financial datasets, design data quality frameworks, perform data validation, and deliver insights through dashboards and reports while collaborating with various stakeholders.

Drive end-to-end campaign execution for assigned accounts: setup, QA, launch, optimization, pacing, and on-call incident response. Monitor campaign health, identify and resolve performance issues, design and run tests, document experiments, and communicate structured updates to managers and Customer Success. Mentor junior analysts and collaborate with product and CS partners to improve outcomes.

Analyze client datasets, build analytical frameworks, validate data quality, design BI dashboards and reports (Zoho Analytics, Power BI, Tableau), lead WBRs/QBRs, communicate insights to clients, map processes, identify revenue opportunities, support risk management, and enable internal stakeholders with standardized reporting.

Lead end-to-end analytics by building and optimizing SQL data models, dashboards, and KPI frameworks. Perform deep-dive analyses on revenue, customer behavior, and operations, deliver actionable insights, and partner with product, growth, and leadership to drive data-informed decisions while ensuring data accuracy and reporting reliability.

Lead AI-augmented analysis and client intelligence: build automated workflows, own dashboards, author automation BRDs, manage data and field BA teams, run QBRs, manage customisation pipeline, and drive upsell documentation and delivery for enterprise clients.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

Perform campaign design, execution, and performance analysis using Python, SQL and ML. Manage and extract data, build reports and insights, collaborate cross-functionally, and present recommendations to clients to optimize marketing campaigns.

Design, develop, and automate BI reports, dashboards, and data models for financial and regulatory decision-making. Own RBI and statutory compliance reporting, optimize complex SQL queries, ensure data quality and governance, and collaborate with Finance, Risk, Compliance, and Tech teams. Drive process automation and explore AI/ML enhancements to improve reporting, anomaly detection, and analytics.

Lead analytics for loyalty and agri-tech: design dashboards, build ETL pipelines, perform segmentation and predictive modeling, ensure data quality and governance, and mentor junior analysts while partnering with product, marketing, sales and ops.

Perform data extraction, cleaning, validation, analysis, and visualization to support business decisions. Build and maintain dashboards and reports, apply statistical techniques to identify trends, assist with predictive models, and present insights to stakeholders. Collaborate with cross-functional teams and support pharma/healthcare analytics and regulatory data standards when applicable.

Analyze customer behavior and campaign performance to generate insights, build scalable data pipelines and automated analytics using SQL, Python, and PySpark, support personalized campaign execution, and collaborate with marketing stakeholders to drive revenue and improve customer experience.

Perform complex data analysis on large datasets using Python and PySpark; build and maintain scalable data pipelines and ETL processes; create reports and visualizations; collaborate with cross-functional teams to deliver data-driven insights; assist with predictive modeling and automate data tasks.

Act as liaison between business and engineering to gather and document requirements, produce BRDs/FRDs and user stories, design and implement scalable data solutions using SQL and Snowflake, participate in SDLC and UAT, and collaborate with product, data, and healthcare operations to ensure release readiness.

Analyze customer behavior and campaign performance to generate actionable insights. Build and maintain scalable data pipelines and automated analytics workflows using SQL, Python, and PySpark. Support campaign planning, audience segmentation, execution tracking, and stakeholder communication to optimize engagement and ROI.

Design, implement, and analyze marketing campaigns using Python and SQL. Extract and manage data, build performance reports and visualizations, provide actionable insights to optimize campaigns, collaborate with cross-functional teams, and communicate findings to clients. Leverage AWS services for data processing and reporting.

Develop and maintain pricing and profitability models, forecast margins, analyze price sensitivity/elasticity and promotional impact, present insights to stakeholders, implement pricing changes, and lead pricing projects. Use marketing mix modelling to assess marketing impact and optimize spend.

Analyze retail data using Python, SQL, and AWS Redshift; develop ML models and Streamlit dashboards; communicate insights to clients; solve problems and support analytics delivery in-office in Bangalore.

Design and analyze A/B tests, segment customers, measure campaign performance, build dashboards, and use SFMC/MCP, Google Analytics, SQL, and Excel to drive personalization and marketing recommendations.

Lead strategic analytics and product delivery efforts: define business strategies, build and execute requirements, oversee multiple projects, partner cross-functionally, develop analytic/ML-driven solutions, and communicate findings to senior leadership to drive growth and operational improvements.

Analyze operational data and processes, identify bottlenecks, design scalable solutions, automate workflows and reporting with Python and SQL, build dashboards and monitoring, perform root-cause analysis, document logic and collaborate with product, engineering, and ops teams to improve automation and data quality.

Analyze user behavior and product performance to deliver actionable insights, driving product decisions. Collaborate with cross-functional teams and create data visualizations to influence product strategy.

The Organic Growth Analyst will support SEO and content strategies for B2B SaaS clients, conduct analyses, and help track performance.

Lead analysis of healthcare and customer data to identify ROI and product value. Build and maintain dashboards, create interactive ROI models, conduct market and competitive research, and communicate insights to commercial, customer success, and product stakeholders.