Top Data Analyst Jobs in Chennai

Provides 24/7 application and data-feed support for centrally hosted pharmacy software. Monitors systems, investigates and resolves technical issues, troubleshoots software, network, database, and data problems, and escalates complex incidents. Collaborates with developers, DBAs, QA, and support teams; documents knowledge; conducts training; coaches team members; and supports customer escalations and projects.

Lead and deliver advanced analytics and machine learning solutions across Sales, Vendor Management, Cloud, eCommerce, Finance, and Supply Chain. Scope projects, build and deploy predictive models, produce executive-ready insights, and partner cross-functionally to drive revenue, operational efficiency, and strategic decisions.

The Data Analyst will deliver analytics, insights, dashboards, data pipelines, transformations, and customer behavioral models for electrification products. Responsibilities include analyzing customer and program performance, identifying business opportunities, presenting recommendations to stakeholders, and supporting data-informed decisions across multiple projects. The role requires independent work, stakeholder engagement, and proficiency with SQL, Python, visualization tools, and Azure-integrated data platforms such as Databricks.

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.

Supports client and settlement instruction data management across onboarding, offboarding, trade execution, and client lifecycle events. Serves as a contact for static data queries, investigates and resolves data issues, improves processing, manages stakeholder expectations, and develops policies and procedures covering AML, KYC, and suitability. Requires financial services experience, analytical and communication skills, relationship management, and proficiency with Microsoft Office.

Leads advanced analytics projects, translating complex data into commercially useful recommendations for clients and internal teams. Develops statistical methodologies, reporting tools, and analytical processes; evaluates data sources; ensures quality and confidentiality; manages project scope and stakeholders; and mentors analysts through training and guidance.

Analyze courier supply and dispatch operations across onboarding, retention, availability, earnings, assignment, acceptance, and delivery success. Build reliable metrics, dashboards, and self-service reporting; identify root causes of performance changes; evaluate experiments, incentives, and product initiatives; validate data quality; and translate findings into recommendations for product, operations, and leadership.

Analyze marketing data to measure campaign performance, ROI, attribution, customer behavior, and funnel conversion. Build Tableau dashboards and reports, define KPIs and measurement frameworks, evaluate experiments, and provide recommendations for campaign strategy and budget allocation. Translate complex findings into executive-ready presentations and collaborate with global marketing stakeholders across digital, social, email, and event channels.

Analyze structured and unstructured data to identify trends, build dashboards and reports, define KPIs, validate data quality, and provide actionable recommendations. The role requires SQL, BI visualization, Excel, relational database experience, and collaboration with business and technical stakeholders. Preferred skills include Python, ETL and data warehousing, cloud platforms, statistical analysis, forecasting, machine learning concepts, and Agile experience.

Leads a team of scientific data analysts supporting Reaxys, Embase, and future AI-enabled life sciences platforms. Oversees search and API quality, data discoverability, testing, feature releases, quality standards, and customer-focused insights. Uses scientific expertise, Python and Bash scripting, databases, cloud platforms, and AI-enabled testing workflows to improve data integrity and platform performance. Coordinates stakeholders, documents work, presents findings, and drives cross-functional projects.

Leads a team of scientific data analysts supporting Reaxys, Embase, and future AI-enabled life sciences platforms. Oversees search and API quality evaluation, data discoverability, testing, feature releases, customer-focused insights, and quality standards. Uses scientific expertise, data analysis, scripting, databases, cloud platforms, and AI-enabled testing workflows to improve platform reliability and relevance. Coordinates stakeholders, advances projects, documents work, and presents recommendations for product and data improvements.

Own analytics and measurement for HighLevel’s AI product portfolio. Define instrumentation standards, feature-level KPIs, adoption and quality metrics, and rigorous approaches for evaluating nondeterministic AI features. Partner with experimentation leaders, PMs, engineering, and Analytics Engineering to close data gaps, influence product roadmaps, establish canonical metrics, and mentor future analysts.

Build and maintain Snowflake ELT/ETL pipelines, enterprise data models, and Streamlit applications supporting global supply chain functions. Develop tested SQL transformations, monitor pipeline health, troubleshoot data quality issues, and implement alerting. Collaborate with analysts and business users to translate requirements into technical solutions while participating in code reviews, documentation, and knowledge sharing.

Audits and validates labeling annotation data for accuracy, consistency, guideline adherence, and regulatory compliance. Identifies errors and root causes, monitors quality KPIs, leads governance cycles, translates data trends into process improvements, and leads the NC Program. Collaborates with agencies and internal stakeholders across labeling operations.

Analyzes and develops software applications across the full development lifecycle, including requirements gathering, technical design, coding, testing, troubleshooting, documentation, deployment, and support. Collaborates with solution architects, project leads, and client teams while following Agile/Scrum practices. Requires strong debugging, problem-solving, communication, consulting, and independent-working skills, plus a bachelor's degree in a relevant technical field.

Maintains and governs account and customer master data across Salesforce and enterprise systems. Responsibilities include creating and enriching records, managing hierarchies, resolving duplicates, investigating data-quality issues, conducting audits, maintaining governance controls and documentation, and partnering with cross-functional teams. The role also supports process improvements, system changes, business transformation initiatives, and provides master data expertise.

Provides research and data-analysis support to economists focused on monetary economics and financial markets in Asia and the Pacific. Responsibilities include preparing publications and presentations, collecting and validating data, reviewing methodologies, developing databases, identifying new data sources, applying advanced analytics, and collaborating on innovation projects. The role bridges economics, data, and technology in a multicultural international environment.

Investigate and resolve complex data discrepancies across multiple systems, validate and reconcile information, perform corrections, document findings, and meet quality and turnaround targets. The role identifies trends and process gaps, supports escalations, conducts peer reviews, guides junior analysts, assists with training, and contributes to process improvements and automation initiatives.

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.

Supports liquidity regulatory reporting controls by documenting data flows, business data elements, lineage, transformations, and controls from booking systems to reporting platforms. Performs SQL-based data analysis, test-case development, functional and business testing, quality remediation, root-cause analysis, requirements management, stakeholder coordination, and management reporting. Contributes to implementation activities, change control, documentation standards, and training junior team members.

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.

Supports hosted e-discovery platforms by loading and transforming data, creating databases and user accounts, configuring permissions, investigating client technical inquiries, and assisting customers through phone, email, and screen sharing. The role also manages internal service-level tasks, collaborates with Engineering, IT, Application, and Project Management teams, and provides platform walkthroughs when needed.

Maintains taxonomies, business glossaries, classification hierarchies, metadata, and testable data rules in a governance platform. Analyzes rule libraries for conflicts, duplicates, and coverage gaps; supports reference data certification, request triage, documentation, governance reporting, and stakeholder enablement. The role ensures governed artifacts are accurate, traceable, auditable, and operationalized across data quality and classification workflows.

Own marketing database operations for EMEA, including audience segmentation, data quality, privacy compliance, and performance analysis. Translate complex marketing data into actionable insights, recurring reports, and segmentation models. Partner with Marketing Operations, IT, and Data teams to improve database accuracy and processes, while enabling stakeholders through clear communication and training. The role requires strong SQL, marketing technology, project ownership, and business-facing analytical skills.

Conduct a three-hour interactive online training session on qualitative data analysis, including thematic and content analysis, coding, codebook development, identifying themes, transcript and focus group analysis, practical case studies, and qualitative analysis tools.