Top Data Analyst Jobs in Mumbai

Manage model onboarding for Citi’s RUBY forecasting platform supporting interest rate risk, CCAR, and financial forecasting. Responsibilities include gathering requirements, developing technical solutions, estimating costs, planning projects, managing risks and resources, prioritizing enhancements, executing forecast processes, and partnering with Finance, Risk, Operations, Technology, and senior stakeholders. The role requires knowledge of data modeling, interest rate risk, financial statements, forecasting, large datasets, and programming or modeling tools.

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.

Research and validate global dividend and index data using multiple sources, investigate discrepancies with data providers, perform quality audits, maintain process and compliance documentation, and collaborate with global stakeholders. The role also supports automation, tool enhancements, data quality initiatives, and index operations while working rotational shifts in Mumbai.

Curates, classifies, tags, and maintains strategic knowledge assets from internal and external sources. Ensures metadata consistency, data quality, confidentiality, governance compliance, repository hygiene, and version control. Uses AI-enabled tools such as NLP, semantic search, document classification, and automated tagging to improve processing and retrieval. Supports consulting teams, generates repository reporting and dashboards, and contributes to knowledge management standards and continuous improvement.

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.

Develop data-driven analytics products using consumer bureau and financial-services data. Responsibilities include data preparation, exploratory analysis, feature engineering, statistical and machine-learning modeling, validation, reusable code development, UAT support, productisation, documentation, and collaboration with Product and Technology teams. The role also requires adherence to data security, model governance, compliance, and quality standards.

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.

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.

Analyze hiring and candidate data to improve decision-making, shortlisting, scoring systems, and operational efficiency. Build dashboards and reports, track hiring funnel metrics, collaborate with operations and product teams, and ensure data accuracy.

Lead HR and people analytics by developing workforce dashboards, reports, and insights covering headcount, attrition, hiring, diversity, engagement, mobility, and costs. Support workforce planning and budgeting, ensure HR data quality and governance, automate reporting, and partner with HR, Talent Acquisition, Finance, and business leaders to provide actionable recommendations and influence workforce decisions.

Analyze business, production, workforce, financial, and operational data to support strategic decision-making. Responsibilities include data cleaning, dashboard and KPI development, project performance analysis, forecasting, workforce planning, profitability analysis, reporting automation, and presenting recommendations to senior leadership. The role partners with Production, Talent Acquisition, Finance, HR, and Studio Operations teams.

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 end-to-end MSME credit-risk analytics, including scorecard and predictive-model development, bureau feature engineering, portfolio monitoring, early-warning analysis, validation, and proofs of concept. Translate analytical findings into client-ready lending recommendations, support pre-sales engagements, review code and models, mentor analysts, and collaborate on product implementation. Ensure solutions are interpretable, stable, well-documented, compliant, and suitable for production monitoring.

Analyze large bureau and client datasets to identify trends, risks, segments, and growth opportunities. Build statistical models, benchmarks, analytical datasets, and automated workflows using Python and SQL. Translate client questions into analytical approaches, validate findings, and communicate insights through charts, reports, and presentations. Maintain documentation, reproducibility, data quality, governance, and peer-review standards while supporting market intelligence and client-facing deliverables.

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.

Leads complex data analytics projects, partners with business stakeholders, and delivers automated dashboards, reports, and strategic insights. Aggregates and validates data, performs data manipulation and stewardship, supports governance initiatives, and improves reporting processes. The role requires advanced Excel, Power BI, Tableau, Salesforce, database, analytics, and dashboard development expertise, along with strong communication, problem-solving, and project coordination 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.

Supports data pipeline development and maintenance, performs basic data engineering and processing tasks, collaborates on data initiatives, follows data quality and security standards, and develops skills under senior team guidance.

Build, maintain, and optimize scalable data pipelines supporting marketing analytics, campaign measurement, brand research, customer segmentation, and insights. Process large datasets, implement data quality controls, resolve systemic errors, support data governance, document data sources, manage production releases, and collaborate with marketing, analytics, technology, and business stakeholders. The role also supports semantic data layers and responsible AI data preparation.

Lead finance analytics initiatives by analyzing large datasets with SQL and BigQuery, identifying trends and inefficiencies, and delivering actionable insights for operational improvement and executive decision-making. Build dashboards, perform ad hoc analyses, automate reporting workflows, define analytical requirements, and collaborate with Finance, Data Engineering, Analytics, and Product teams.

Develops and standardizes commercial dashboards, reports, and analytics to support business decisions. Aggregates and validates data from multiple sources, maintains data integrity, manages reporting requests, and recommends process improvements. The role also supports data stewardship and governance initiatives, improves data adoption and maintenance, and resolves duplicate or improperly assigned records. Collaboration with stakeholders, data manipulation, dashboard creation, and business insight generation are central responsibilities.

Build, maintain, and optimize enterprise data platforms using Databricks, Spark, cloud technologies, and DevOps practices. Develop CI/CD pipelines, support cloud migration and automation, monitor platform health, troubleshoot incidents, and ensure reliable, secure, and scalable data services. Participate in rotational production support across global time zones, perform root cause analysis, maintain operational documentation, and collaborate with engineering, architecture, product, and business teams.

Lead oncology patient-journey, line-of-therapy, brand, HEOR, and healthcare resource utilization analytics using structured claims and patient data. Build SQL pipelines, perform exploratory and statistical analyses, ensure data governance and reproducibility, and translate findings into dashboards and client-facing insights. Collaborate with HEOR, market access, strategy, and engineering teams while independently managing project delivery and stakeholder communication.