Top Data Analyst Jobs in Pune

Lead SOX compliance and ICFR activities including internal controls design, risk assessment, audit coordination, governance reporting, operational effectiveness, and stakeholder communication.

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.

Analyze large datasets to identify trends, correlations, data-quality issues, and improvement opportunities. Build data pipelines, logical data models, dashboards, visual reports, and automated reporting processes. Translate analytical findings into business recommendations, support risk and control activities, and collaborate with stakeholders. The role also requires payments-domain knowledge, software development lifecycle delivery, and familiarity with cloud, CI/CD, machine learning, and AI concepts.

Perform business process mapping and requirements elicitation (BPMN 2.0), design 'To be' solutions, produce BRDs, use cases, user journeys and acceptance criteria, support TOM and foundation data initiatives, drive process improvements using Lean/Six Sigma, document processes, conduct training, and collaborate with stakeholders to translate business needs into application and operational requirements.

Analyzes large datasets to identify trends, correlations, data-quality issues, and actionable business insights. Builds data pipelines, logical data models, interactive dashboards, visual reports, and automated reporting processes. Partners with stakeholders to recommend operational improvements, strengthen controls, and support data-driven decisions. The role also involves data integration, engineering, analytics, machine learning fundamentals, and payments-domain knowledge.

Lead analysis of large datasets to improve data quality, lineage and controls; build automated data pipelines; apply advanced analytics and ML to surface insights; design interactive dashboards and automated reports; translate findings into actionable business recommendations and drive process improvements while coaching and influencing stakeholders.

Supports EDI configuration and business processes for North American sales organizations. Monitors and troubleshoots inbound and outbound transactions, maps data between internal systems and standardized EDI formats, manages access, and ensures compliance with industry rules. The role reports EDI KPIs, maintains process documentation, analyzes customer requirements, and applies Lean continuous-improvement methods to reduce errors and improve touchless order flow.

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.

Support Finance and Central Operations by building dashboards, reporting, automated data pipelines, reconciliations, controls, and analytics. Analyze revenue, expenses, margins, cash flows, payment volumes, disputes, exceptions, and processing performance. Partner with Finance and Payment Operations to investigate discrepancies, automate workflows, improve data quality, and translate business questions into reliable models and actionable insights.

Develop and deliver AI/ML solutions by building supervised and unsupervised models, deep learning systems, NLP and LLM applications. Responsibilities include LLM fine-tuning, prompt engineering, RAG, vector databases, transformer architectures, and AI agent deployment. The role requires partnering with business stakeholders, presenting technical findings, and continuously learning emerging AI technologies.

Build and maintain internal business intelligence dashboards covering revenue, profitability, headcount costs, and team utilization. Support leadership, Finance, and HR with ad hoc analysis and planning insights. Maintain data hygiene and a single source of truth for business metrics, translating raw data into clear recommendations.

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.

Develop and maintain interactive Tableau dashboards and reports that turn complex data into actionable business insights. Extract, transform, and analyze data from multiple sources using SQL, identify trends, troubleshoot data issues, and support data visualization best practices. Collaborate with business stakeholders to translate analytical needs into clear visual solutions and recommendations for nontechnical audiences.

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.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

The Data Analyst will support product marketing initiatives by analyzing data, tracking KPI progress, developing dashboards, and providing actionable insights to inform decision-making across business units.

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.

Extracts, analyzes, validates, and abstracts clinical data from EHR/EMR systems for registries, reporting, and quality improvement programs. Reviews pathology, radiology, and treatment reports; maintains high accuracy and inter-rater reliability; protects patient confidentiality under HIPAA; prepares reports; and supports quality assurance activities. Requires advanced medical terminology knowledge, clinical data expertise, attention to detail, and independent work capabilities.

Develops and maintains Power BI dashboards, KPI reports, and data solutions for Global Business Services. Responsibilities include data collection, validation, analysis, quality improvement, stakeholder collaboration, workflow automation, and SharePoint support. The role uses Power Query, Power Platform tools, Excel, and potentially SQL or Python/R to improve reporting accuracy and operational efficiency. Success requires strong communication, problem-solving, ownership, learning agility, and continuous improvement.

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.

Design and independently deliver data analytics projects, using advanced statistical and programming techniques across complex data sources. Develop scalable solutions, visualize and communicate findings, recommend business actions, and influence implementation. Lead junior analysts, collaborate with technical and nontechnical stakeholders, explore data monetization opportunities, and ensure compliant use of data assets through governance partnerships.

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.