Top Data Analyst Jobs in Delhi

Build and maintain clinical site payment forecast models, link forecasts with Medidata Payments, analyze plan-versus-actual variances, reconcile study closeouts, support audits, and produce accurate client-ready financial reports. The role collaborates with clinical operations, revenue recognition, clinical payments, investigator grants payments, and project teams while ensuring compliance with accounting, revenue recognition, and sponsor requirements.

Creates, updates, and maintains material master data and parts records in SAP and IFS. Collaborates with BOM, procurement, engineering, manufacturing, and compliance teams to collect and validate information. Reviews data quality, resolves inconsistencies, maintains documentation, monitors KPIs and SLAs, ensures turnaround-time compliance, and identifies process improvements while supporting regulatory and company data standards.

Analyzes, transforms, validates, and manages SAP and business data in cloud environments. Develops reports, dashboards, and analytical solutions; performs data quality, cleansing, reconciliation, migration, and troubleshooting activities. Collaborates with business stakeholders and SAP functional and technical teams to define requirements, resolve reporting issues, document processes, and present actionable insights.

Analyze and interpret large healthcare datasets, build and maintain data pipelines and structures, collaborate with cross-functional teams to deliver actionable insights, and document data processes and analyses.

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.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

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 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.

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.

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.

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.

Build, tune, deploy, and validate machine learning models for fraud detection, risk scoring, and customer analytics in the BFSI and credit card domain. The role involves performance and stability testing, documentation, troubleshooting data and model issues, communicating findings to varied stakeholders, managing analytical projects independently, and staying current with emerging AI and ML techniques.

Supports fundraising and donor management analytics during a six-month internship. Maintains donor and campaign databases, cleans and validates data, builds Excel trackers, dashboards, and reports, analyzes donor and campaign trends, and presents actionable findings to leadership. The intern also documents datasets and reporting tools and delivers a comprehensive final analysis report with strategic recommendations.

Internship data analyst supporting dashboard monitoring, user behavior and content ecosystem analysis, A/B test evaluation, campaign performance analysis, data quality assurance, and metric documentation. The role uses SQL and Excel to derive insights on engagement, retention, conversion, and creator ecosystems, while collaborating with product and operations teams in a blockchain and digital assets environment.

Own business data as a trusted source of truth by building metrics, dashboards, reporting systems, and analytical frameworks. Analyze complex datasets with advanced SQL, define KPIs, identify trends and opportunities, and solve ambiguous business problems. Partner with business, marketing, finance, and other teams to translate analysis into clear recommendations and data-driven decisions.

Build and maintain logistics data pipelines, dashboards, and reports; validate and cleanse datasets; translate business requirements into scalable data models; perform analysis to identify trends and root causes; align metrics with global KPIs and governance; prioritize analytics demand and partner with cross-functional teams to improve visibility and logistics performance.

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.

Analyzes D2C, marketplace, and quick-commerce channel profitability, including unit economics, margins, trade spend, discounts, returns, and write-offs. Performs budget variance analysis, builds MIS reports and dashboards, automates reporting, identifies margin leakage, and supports pricing, forecasting, inventory planning, and working capital optimization. Collaborates with Supply Chain, Sales, Operations, and Growth teams to provide financial insights and flag business risks.

Develop and execute SAP data conversion programs for implementation projects. Perform legacy-to-SAP field mapping, transformation, and loading of master and transactional data using BODS, BAPIs, and IDOCs. Create validation and reconciliation reports, troubleshoot conversion defects, support testing and Go-Live activities, prepare technical documentation, and identify automation opportunities.

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.

Supports data engineering initiatives that make raw data usable and accessible. Works on moderately complex projects, applies technical concepts to identify solutions, resolves technical issues, and contributes to data acquisition, integration, provisioning, analytics platforms, and business intelligence capabilities.

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.

Analyze large-scale datasets to generate actionable business insights, define and monitor KPIs, build dashboards and automated reports, maintain data pipelines, and investigate anomalies across ad delivery, bidding, monetization, campaigns, traffic quality, and platform performance. Collaborate with product, engineering, operations, and business teams to support strategic and real-time decisions.

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.