Top Data Analyst Jobs in Kolkata

Perform gap analyses across trading data from multiple source systems, identify discrepancies, build automated reports using Python and SQL, create visualizations (Power BI or Python libraries), present findings to stakeholders, and coordinate with upstream/downstream teams to implement logic and document requirements.

Audit and analyze telecom client invoice data to find billing discrepancies, apply audit methodologies, review contracts/tariffs, use industry databases and tools, document claims, and support reconciliation and vendor interactions to resolve disputes.

Analyze telecom data sources (quotes, orders, invoices, provisioning systems) to identify disconnected circuits, manage findings lifecycle, validate vendor responses and credits, and use tools like KNIME and Business Objects. Develop SME knowledge of client systems and apply audit principles, pattern recognition, and cross-referencing to resolve disputes.

Register and assist job seekers on the company job portal, support resume uploads, collect candidate information, provide phone support during specified hours, and perform basic data entry and system updates for recruitment processes.

This posting asks candidates to register on JobDials.com for a client: create an account, upload your resume/CV, and call the listed contact between 11 A.M. and 2 P.M. for instant support. The description promotes portal features (resume database, job alerts via email/SMS) but provides no Data Analyst responsibilities or qualifications.

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.

Design, develop, and support analytics solutions, dashboards, reports, and data models. Prepare and transform data, ensure data quality and governance, collaborate with stakeholders, leverage AI to accelerate delivery, and drive process improvements to enable data-driven decisions.

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.

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.

Seeking a Data Analyst with 6-9 years' experience in Python-driven data analysis or automation. Must be strong in Python programming, basic AWS, shell scripting, and Linux to build analysis scripts, automate workflows, and operate in Linux/AWS environments.

Senior Data Analyst role based in Chennai or Bangalore requiring strong SQL and visualization skills (Power BI or Tableau). 8+ years experience required. Python and PowerAutomate familiarity preferred. Responsible for analyzing data, building dashboards, and supporting reporting and automation.

Conduct consultative analytics and deliver executive-level recommendations and ad hoc analyses to business and finance partners. Build self-service dashboards and presentations, perform predictive modeling and time-series forecasting (preferably for workforce optimization), provide cost-benefit analyses for investments, and streamline processes while communicating insights to senior stakeholders.

Perform consultative analytics and predictive modeling to produce executive-level recommendations and ad-hoc analyses. Build dashboards and presentations for senior management, support finance and business partners with cost-benefit and workforce optimization analyses, streamline processes, and communicate insights clearly to influence decision-making.

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.

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.

Drive end-to-end product analytics for user growth and product strategy: define metrics, design and analyze A/B tests, handle PB-scale behavioral and transactional data, build dashboards, predictive models, and deliver actionable insights to product and business stakeholders.

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.

Entry-level Product Data Analyst internship supporting product analytics: build and analyze conversion funnels, evaluate A/B tests, create dashboards, respond to ad-hoc data requests, write SQL pipelines, monitor data quality, and translate findings into visual summaries to inform product decisions.