Top Data Analyst Jobs in Los Angeles, CA

Supports fintech partnership financial analytics through deal modeling, profitability analysis, forecasting, KPI monitoring, budget tracking, variance analysis, and executive reporting. Evaluates deposit balances, net interest income, fee revenue, pricing, and client economics across gaming, payments, acquiring, issuing, and banking-as-a-service verticals. Collaborates with Sales, Account Management, Finance, Treasury, Data teams, and leadership to inform deal decisions and improve portfolio performance.

The Senior Data Analyst develops advanced SQL analyses, maintains Tableau and Hex dashboards, validates warehouse metrics, and translates data into actionable recommendations for executives, funders, government audiences, and community partners. The role emphasizes data storytelling, reporting standards, secure PII-aware delivery, stakeholder collaboration, and business impact evaluation. It also offers growth into AI-assisted analytics, custom visualization, and data-to-report automation.

Analyze and connect complex datasets to generate actionable business insights and improve data products. Gather and manage requirements, document processes, define acceptance criteria, support testing, and collaborate with engineering and data teams. Serve as a data subject matter expert while advancing data quality, stewardship, lineage, metadata management, and stakeholder alignment across digital, direct-to-consumer, sports, fan, and business use cases.

Runs end-to-end data readiness assessments across enterprise source systems, including source connections, scans, profiling, quality analysis, scorecards, issue lists, and migration baselines. Validates findings with SQL, investigates defects, evaluates duplicates and sensitive data, establishes tolerances, and translates results into migration design, effort, and reconciliation decisions while collaborating directly with client data stewards.

Leads paid media analytics by integrating data from advertising platforms, building scalable data models and automated dashboards, maintaining tracking and attribution systems, and developing performance benchmarks. Partners with Paid Media, Marketing, Product, Engineering, and Data teams to evaluate campaigns, optimize budgets and targeting, conduct tests, and deliver actionable recommendations related to ticket sales, event awareness, and customer acquisition.

Own financial forecasting, predictive modeling, P&L reporting, unit economics, variance analysis, and reconciliation across e-commerce payment and accounting systems. Build financial datasets, SQL models, dashboards, and predictive models using Python and Snowflake. Partner with Finance and executive leadership to explain forecasts, assumptions, risks, and discrepancies while mentoring analysts and improving financial data quality.

Lead research and thought leadership on data management and AI readiness, produce actionable insights, advise clients and sales, present at events, mentor analysts, and improve research processes to drive client outcomes.

Analyze and model marketing, product, and loan application data to optimize the borrower funnel and drive growth. Build BigQuery datasets, dbt models, and Tableau dashboards; evaluate customer behavior, acquisition costs, approval rates, and origination performance. Partner with Product, Marketing, and Engineering on A/B tests, statistical analysis, and actionable insights for leaders. Apply lending and fintech knowledge to improve conversion, customer value, and portfolio outcomes.

The Investment Technology Business Analyst will deliver front-office technology and data implementations for asset and wealth management clients. Responsibilities include business analysis, SQL-based data work, data modeling, governance and quality management, cloud data platform implementation, and expertise across investment processes such as risk, performance, compliance, reporting, derivatives, operations, or investment data. The role also involves leading small to medium-sized consulting teams, developing technical solutions, managing client relationships, and traveling as needed.

The Data Management Analyst advances data governance, organizational change management, and data fluency initiatives. Responsibilities include defining data requirements, preparing and analyzing datasets, developing dashboards and reports, communicating insights, supporting governance adoption, and improving recurring data processes through automation. The role may lead project components, develop advanced visualizations and analytical models, and coordinate contributors. Work is performed onsite in East Aurora, New York, or Torrance, California, with less than 10% travel.

Performs treasury finance operations, including loan sales, data analysis, reconciliation, and financial controls. Automates recurring workflows using SQL, Python, Excel, and AI tools; maintains and modernizes data pipelines; investigates discrepancies; and communicates insights to technical and business stakeholders. Serves as a subject matter expert on loan data and finance processes while supporting fraud prevention and financial governance.

Leads marketing measurement strategy through geo holdout and incrementality testing, forecasting, experimentation, and statistical analysis. Partners with Marketing, agencies, and Data Science to guide channel budgets and campaign decisions. Queries large-scale data using SQL and Python in Databricks and BigQuery, develops measurement models, automates analyses with AI tools, and mentors analysts while providing technical leadership.

Provides data analysis and reporting support for the health vertical. Responsibilities include creating visualizations, automating reports and audits, analyzing web, email, and app engagement data, conducting retention and A/B testing analyses, supporting time-sensitive business requests, and developing expertise in assigned business areas. The role also evaluates how AI can improve analytical workflows and requires collaboration across project teams.

Analyzes workforce and business data, investigates customer questions, ensures data quality, prepares reporting deliverables, and presents actionable insights. Partners with customers and internal teams to manage multiple projects and priorities. Develops Python and SQL-based tools and automations to streamline recurring processes while documenting methodologies and resolving data discrepancies.

Performs data reconciliations, validation, quality assurance, and root-cause analysis for mortgage and regulatory reporting. Develops reconciliation, exception, management, and operational reports; investigates discrepancies; coordinates corrective actions; documents procedures and controls; supports audits and regulatory examinations; and identifies automation and process-improvement opportunities using Excel, Power BI, SQL, and generative AI tools.

Extracts, transforms, and loads data from diverse sources; develops Power BI dashboards and reports; maintains data governance, quality, lineage, metadata, security, and retention practices; documents ETL processes, APIs, and reporting solutions; trains stakeholders; troubleshoots data pipelines; and identifies opportunities for automation and process improvement.

Supports enterprise data catalog development by profiling datasets, documenting definitions, and labeling data. Engineers and tests features improving AI and machine-learning model accuracy across business functions, and designs prompts for AI agents while evaluating response quality and failure cases.

Deliver recurring and ad hoc commercial analytics, client reporting, performance-guarantee calculations, dashboards, and value measurement. Define and govern metrics, validate data, improve documentation and workflows, and automate repeatable processes. Partner with Client Success, Commercial, Finance, Product, and Analytics teams to translate complex questions into actionable insights, client-ready narratives, and recommendations that strengthen client relationships and inform business strategy.

Analyze business performance, develop hypotheses, answer critical business questions, and build dashboards and reports in Sigma. Support budgeting, forecasting, data quality checks, and reconciliations while partnering with teams across growth, product, insurance, finance, and leadership. Serve as a trusted data advisor by answering metric and reporting questions and promoting data-driven decision-making.

Manages clinical trials data applications, pipelines, integrations, cloud data architecture, reporting, and informatics structures. Develops schemas, custom reports, data transformations, and visualizations; supports OnCore, eRegulatory systems, REDCap, Snowflake, Fabric, and APIs. Collaborates with technical teams, clinical research staff, leadership, and vendors; provides training, documentation, application support, data quality oversight, and technical leadership for datamart development and reporting initiatives.

Supports risk portfolio programs through strategic project planning, data analysis, dashboard development, process automation, vendor and ROI management, governance, and audit documentation. The role partners with risk analysts, data scientists, Product Management, Engineering, and other stakeholders to identify risk indicators, design controls, improve workflows with AI tools, and communicate actionable insights across credit, fraud, and reputational risk initiatives.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

Manage a team of 2–3 analysts while remaining hands-on with SQL, dbt models, dashboards, and complex operational analyses. Lead ambiguous, cross-functional initiatives, deliver recommendations to senior stakeholders, ensure data quality, and improve reporting automation. Partner on AI analytics strategy, data readiness, agent evaluation, and human-in-the-loop governance. Responsibilities include coaching, prioritization, performance management, technical review, KPI development, and operational insights across customer experience, fraud, payments, workforce management, and VIP functions.

Monitors, validates, and improves data quality across device, program, operational, and field sources. Designs automated checks, reconciles discrepancies, investigates root causes, documents findings, and communicates impacts and recommendations. Collaborates with analytics, engineering, MEAL, and country teams to resolve issues. Maintains reproducible analyses using SQL, programming, version control, and notebooks while supporting data governance, reporting standards, and responsible handling of sensitive information.

Maintains data governance and quality across mission systems by validating sources, managing metadata and data dictionaries, reconciling metrics, performing profiling and cleansing, documenting lineage, and supporting cross-system harmonization. The analyst collaborates with reporting teams, dashboard developers, data owners, and PMO leadership to ensure accurate, standardized, compliant enterprise reporting.