Data Analyst

• Partner with Product, Marketing, and Leadership to identify opportunities, influence product strategy, and drive business decisions through data
• Drive end-to-end product and growth analyses, including funnel analysis, cohort analysis, retention, segmentation, monetization, and experimentation
• Define success metrics and evaluate the impact of new features, experiments, and product initiatives
• Develop dashboards, recurring reports, and self-service analytics
• Collaborate with engineers to design, implement, validate, and maintain product event tracking within React-based interfaces
• Identify and troubleshoot tracking issues affecting data integrity
• Integrate data from Amplitude, Google Ads, Meta Ads, payment systems, CRM, and other sources to create a unified business view
• Document key metrics, tracking plans, and data definitions

Senior Data Analyst – Product Analyst

• Deliver analyses and dashboards to customers and internal stakeholders to communicate Spring Health’s impact
• Analyze different data sources, build expertise, and develop creative stakeholder-focused solutions
• Develop a deep understanding of Spring Health products and their impact narratives
• Collaborate with Product to evolve the customer data story and expand standard reporting
• Identify opportunities to automate and scale commonly requested reports and data sets
• Work with the data stack, including Snowflake, Looker, dbt, and Hex
• Review reports and data sets for consistency and quality
• Complete requests promptly while maintaining high quality
• Bring ideas that reduce manual data pulling
• Support dashboards and analyses that deliver ongoing stakeholder value

Data Analyst II, Customer Reporting

• Lead the Enterprise Data, Analytics & AI team within Silicon One Business Operations
• Set the technical direction and roadmap while fostering high performance and professional growth
• Partner with cross-functional leaders to translate ambiguous business needs into scalable data and AI solutions
• Manage priorities, risks, and investment tradeoffs
• Define secure, governed, and AI-ready data architecture
• Build reliable, reusable data products with high standards for quality, lineage, and traceability
• Lead predictive modeling, anomaly detection, and forecasting initiatives for product planning, capacity, and risk management
• Identify and deploy production-ready AI agents and workflow automation
• Establish responsible AI standards covering security, observability, and cost-efficiency
• Lead delivery of self-service BI products and executive dashboards for operational and financial performance
• Hire, coach, and develop a high-performing team of technical contributors
• Provide mentorship and hands-on technical guidance

Director, Enterprise Data, Analytics, AI

• Provide support for pharmacy financial, operational, and clinical data analytics
• Support Associate Directors in interpreting and analyzing data results
• Provide ongoing reports
• Develop and implement databases and data collection systems
• Develop data analytics and other strategies that optimize statistical efficiency and quality
• Extract data from primary or secondary data sources
• Maintain databases and complex data systems
• Filter and clean data by reviewing reports and performance indicators to locate and correct code problems
• Work with management to prioritize business and information needs and improvement opportunities
• Initiate and implement Medical Center and departmental resource management initiatives

Pharmacy Program Coordinator, Data Analytics

• Ensure the integrity, accuracy, and operational reliability of client and account data across Salesforce and Entity Master platforms
• Perform manual reconciliation of data discrepancies between CRM and Master Data Management
• Resolve data breaks impacting onboarding blockers, operational workflows, and sync failures
• Support development of automated reconciliation capabilities
• Investigate record merges, duplicate records, conflicting attributes, missing MDM records, and contact conflicts
• Conduct root cause analysis and recommend scalable systemic solutions
• Track and monitor reconciliation issues and patterns
• Develop reporting on issue volume, trends, and business impact
• Escalate systemic issues to Salesforce Engineering, Data Engineering, or Data Operations
• Query, analyze, and remediate data using SQL, SOQL, and Excel
• Perform validation and reconciliation across multiple data sources, including Snowflake
• Apply business context to reconciliation decisions and prioritization
• Document reconciliation processes, issue types, and resolution steps
• Build process guides, playbooks, and onboarding materials
• Identify opportunities to streamline workflows and reduce manual effort
• Partner across business, data operations, and IT Engineering teams
• Bridge business users and technical teams to resolve data issues

Vice President, Senior Data Analyst – SMA Solutions

• Assist in developing, maintaining, and executing statistical models in SAS or a comparable system
• Recommend revisions and improvements to existing statistical models
• Conduct and document detailed analyses and report findings to management for stress testing, capital planning, and budgeting
• Update, maintain, and evaluate statistical and predictive models to identify historical trends and forecast future performance of credit losses, loan originations, pre-provision net revenue, and related measures
• Analyze models, challenge assumptions, evaluate performance and robustness, and write code, reporting, and validation documents
• Present findings to management
• Perform and document quantitative assessments of model theory, design, implementation, data integrity, and reliability
• Keep up-to-date with industry best practices and emerging trends in statistical analysis and modeling
• Create reports and presentations communicating findings to model owners and stakeholders
• Perform data checks and validations and communicate data quality concerns
• Apply statistical techniques to analyze data, forecast, interpret, and quantify trends
• Update and aid in developing risk and regulatory reporting, stress testing schedules, capital plan reports, presentations, and narratives
• Collaborate with senior analysts and Credit Union team members on project requirements, data needs, and deliverables
• Perform other duties as assigned
• Comply with regulatory compliance and assigned training requirements, including applicable BSA regulations

Statistical Data Analyst

• Own and maintain the authoritative marketing data model and metric definitions
• Deliver end-to-end marketing measurement as business-focused stories with recommendations
• Partner with commercial, product and digital marketing leaders to diagnose channel performance, funnel leaks and segment opportunities
• Own lead quality measurement, including MQL definitions, lifecycle metrics and lead scoring validation
• Build self-serve datasets and documented endpoints for marketing leaders
• Deliver curated visuals, recurring digests and narrative summaries for stakeholders
• Validate self-served numbers and establish automated data-quality checks
• Build AI-assisted analytics tools and maintain the marketing semantic layer and metric dictionary
• Steward the governed Snowflake marketing data product layer
• Represent marketing analytics requirements as the technology stack evolves, including Salesforce Marketing Cloud migration, Segment instrumentation and e-commerce replatforming
• Drive campaign performance reporting adoption and support the migration from Marketo to Salesforce Marketing Cloud

Marketing Analytics Manager

• Design, build, and maintain scalable data pipelines on AWS to support CPM reporting and analytics
• Execute ETL processes to assess client datasets and present data in consumable formats for business stakeholders
• Perform data analysis and produce technical reports and findings supporting program and project decision-making
• Develop and maintain reporting tools, dashboards, and data automation workflows
• Interpret trends, implement leading practices, and deliver actionable insights aligned with client business objectives
• Lead departmental data process initiatives and support cross-functional data efforts
• Provide data visualization support across program and project workgroups
• Collaborate with CPM analytics team members on AWS platform buildout, including migration of SAP HANA views to AWS tables

Infrastructure & Capital Projects – Data Analyst III

• Analyze data across multiple marketing technology platforms, including CRM and ERM systems, marketing automation, social media analytics, and website traffic sources, to generate insights on key marketing metrics
• Design and implement dashboards for marketing, business development, and leadership teams to track and evaluate KPIs
• Deliver strategic recommendations to optimize marketing initiatives and support client acquisition and retention efforts
• Collaborate with business development to develop data signals and indicators supporting client prospecting, relationship building, and cross-selling opportunities
• Manage Salesforce administrative tasks, including creating triggers, setting dependencies, developing automation flows, and conducting regular audits
• Audit and update Salesforce custom objects, fields, relationships, sharing rules, profiles, and permission sets
• Develop and execute quality assurance plans for data syncs and field mappings across integrated systems
• Identify opportunities for data enrichment services addressing missing or incomplete data
• Assist with implementation workflows for migration and integration of data sources and marketing tools
• Monitor data quality and troubleshoot discrepancies across marketing systems
• Provide onboarding and ongoing user support, troubleshoot system issues, and drive adoption of best practices
• Develop training documentation and instructional materials, including video tutorials, and lead formal training sessions

Data Analyst, CRM

• Develop and document instrumentation and experimentation standards
• Partner with product engineering teams to apply standards to priority product development work
• Build and improve scalable analysis pipelines and tooling
• Produce reliable insights and strengthen understanding of data structures and metrics
• Create tools and processes for self-service access to trusted datasets, insights and metric definitions
• Identify data quality and discoverability gaps and advocate for targeted improvements
• Maintain documentation for tools, datasets, metrics and operating practices
• Partner with Product, Engineering, Data Science, Data Engineering and Business Intelligence teams
• Communicate actionable insights and inform product improvements
• Use AI to accelerate analysis, prototyping and iteration while verifying correctness, quality and responsible use

Data Analyst jobs in California