Top Data Analyst Jobs in Kolkata

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.

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.

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

The Senior Analyst will own Pricing Tools, manage data governance, drive pricing strategy decisions, execute audits, and enhance operational effectiveness.

Ensure accuracy, completeness, and integrity of Salesforce customer and account data. Build automated validation and enrichment pipelines (SQL/Python), perform large-scale cleansing and deduplication (DemandTools, Data Loader), create monitoring dashboards (Power BI), enforce governance, and apply AI/LLMs to improve matching, classification, and anomaly detection so data never blocks Quote-to-Cash processes.

The role involves supporting and maintaining the Azure Data Platform by managing incidents, monitoring performance, and optimizing database operations. Responsibilities include troubleshooting ADF, Synapse Analytics, and ensuring data security compliance.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.