Top Data Analyst Jobs in Chennai

Gather, clean, and analyze data from multiple sources; build and maintain Power BI and Excel dashboards; run SQL queries and Python scripts for automation; collaborate with cross-functional teams to interpret trends and communicate insights; create documentation and improve reporting processes.

Perform exploratory analysis, build dashboards and reports (Tableau), write SQL queries, use Python for data cleaning and predictive models, collaborate with stakeholders, communicate insights, and maintain data models, pipelines, and quality checks.

Develop and maintain business intelligence solutions for Asset Protection, Inventory Control, and Claims teams. Build Tableau dashboards, Snowflake datasets, Alteryx workflows, and data pipelines using SQL and related tools. Analyze shipment, inventory, claims, carrier, and loss data to identify trends, root causes, and operational risks. Troubleshoot data quality issues, validate reporting, document processes, support claims recovery, and collaborate with analytics and engineering teams on scalable reporting solutions.

Supports client operational and analytical processes by executing procedures, validating deliverables, identifying process improvements, coordinating stakeholders, testing updated workflows, documenting operational models, researching issues, and investigating client questions. Collaborates with senior analysts, delivery leads, engineering teams, and internal stakeholders to provide accurate, timely client results across multiple tasks and time zones.

Supports client operations through data analysis, process execution, quality validation, reporting, secondary research, and investigation of client questions. The role coordinates stakeholders across time zones, documents and tests operational procedures, identifies process improvements, and collaborates with engineering and delivery teams to ensure accurate, timely client deliverables.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

Own data quality and root-cause analysis for prediction issues: detect anomalies, trace sources, fix processes, automate QA/reporting with Python and SQL, maintain dashboards, and partner with Data Science, Engineering, Product, and Commercial teams to improve prediction performance and customer-facing analytics.

Support data integrations and quality by checking ingested/system-generated data for anomalies, building and running QA checks and automations with Python and SQL, assisting on customer data queries and dashboards, and documenting findings to improve prediction reliability.

Early-career Data Analyst who designs and owns core analytics, dashboards, and data pipelines. Analyze transaction, customer, and credit data to inform credit, fraud, AML, portfolio performance, unit economics, and growth. Build automations and workflows with SQL and Python, partner with cross-functional teams, and own compliance reporting and durable analytical systems.

Supports Workday employee data migration by preparing and validating EIB files, coordinating data loads, maintaining cutover plans, tracking project actions and issues, reconciling source and migrated data, and supporting go-live activities. The role also maintains migration documentation, status reports, trackers, and handover materials while coordinating with HR, Payroll, IT, Workday teams, and other stakeholders.

Evaluates, acquires, and manages external healthcare and pharmaceutical data sources for Roche’s U.S. commercial and strategic teams. Translates stakeholder needs into data requirements, assesses vendors and datasets for quality and business fit, investigates data issues, maintains documentation, and supports dataset onboarding and investment decisions. The role requires collaboration with U.S. stakeholders, external vendors, and cross-functional teams, along with structured analysis, stakeholder management, and knowledge of pharma and healthcare data ecosystems.

Support Applied AI team by writing production-quality Python and optimized Snowflake/SQL queries to prepare and validate large datasets, run EDA, build evaluation datasets and benchmarking, and assist product managers and data scientists with experimentation, root-cause analysis, and ML/AI pipeline evaluation. Document and communicate findings to stakeholders.

Support AI workflows by building and optimizing Snowflake SQL, writing production-quality Python for data transformation and pipelines, curating evaluation datasets and metrics, performing exploratory data analysis to find quality issues, and partnering with product managers and data scientists to support experimentation, model evaluation, and automation.

Design, build, and govern HSW data solutions and analytics; deploy AI and automation into HSW processes; produce Power BI dashboards and regular reports; support Cority operations; drive data strategy, governance, and actionable insights to improve safety and operations.

The Senior Data Analyst will define source data, create data mapping, report inconsistencies, assist with data migration, and manage stakeholder expectations while delivering insights in financial services.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

The role involves building scalable data models, automating reporting, implementing metrics, developing dashboards, and ensuring data quality across teams globally.

Support development and maintenance of SQL-based data pipelines and analytics workflows. Assist data standardization, build and optimize data models, dashboards, and reports. Perform ad-hoc analyses, monitor data quality, implement validation logic, and collaborate on cross-functional data and risk projects under mentorship.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Lead data science projects: analyze banking data, build ML solutions, design data displays, consult with stakeholders, manage requirements-to-implementation, coach junior staff, and ensure compliance and data quality.

Lead the data solutions strategy for PR&C PSP division, managing data initiatives, teams, and collaborating on analytics projects. Ensure compliance, governance, and optimize data services while communicating technical solutions to stakeholders.

Design and scale transportation analytics and tooling to optimize network performance and reduce shipping costs. Build dashboards, routing/ship-speed optimizers, chargeback/dispute systems, and cost benchmarking engines. Deliver predictive and real-time KPIs, automate processes, improve data accuracy, and provide fast ad-hoc decision support for cross-functional stakeholders.

Monitor and validate market data deliveries, batch processes, and feeds for SaaS clients. Troubleshoot data quality and technical issues, manage incidents, coordinate releases and production patches, and support API-related client queries. Develop standard operating procedures, automate manual checks using Python, engage vendors, and lead post-mortem and root-cause analysis activities. The role requires financial markets knowledge, especially derivatives and multiple asset classes, along with Excel, SQL, troubleshooting, and communication skills.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.