Matrix Global

Marketing

• Develop and execute an integrated marketing strategy focused on pipeline generation and revenue growth
• Own lead generation programs across digital, content, email, webinars, events, and partner channels
• Manage marketing funnel performance from awareness through opportunity creation
• Drive account-based marketing initiatives targeting key industries and strategic accounts
• Monitor and optimize campaign performance using data-driven insights and analytics
• Lead the company's social media strategy across LinkedIn and other relevant platforms
• Develop content that strengthens brand awareness and market positioning
• Manage website messaging, SEO, SEM, paid campaigns, and conversion optimization initiatives
• Track engagement, lead generation, and conversion metrics
• Build thought leadership programs for executives and subject matter experts
• Establish and grow strategic partnerships with technology vendors, consulting firms, industry associations, and channel partners
• Develop joint marketing initiatives, co-branded campaigns, webinars, and events
• Identify opportunities to expand market reach through alliances and partner networks
• Collaborate with sales leadership to maximize partner-driven pipeline opportunities
• Build and scale marketing programs supporting company growth objectives
• Partner with Sales, Product, Customer Success, and Executive Leadership
• Manage the marketing budget and evaluate ROI across initiatives
• Implement processes, reporting, and KPIs to measure marketing effectiveness
• Stay current on industry trends, competitive activity, and emerging marketing technologies
• Drive qualified pipeline, marketing-sourced revenue, inbound demand, digital engagement, and measurable partnership impact

Marketing Leader

Full-stack Engineer

• Execute the full software development lifecycle to build integrations and enhancements
• Write clean, testable code
• Integrate software components into fully functional systems
• Troubleshoot, debug, and upgrade existing systems
• Deploy and support systems in production environments
• Monitor performance and stability using dashboards and alerts
• Follow Agile practices and contribute to sprint planning and task refinement
• Ensure smooth feature deployment and product upgrades
• Collaborate with Data Scientists, Project Managers, and Fraud Analysts to understand client needs
• Translate client needs into technical requirements
• Deliver robust, scalable solutions and support client success
• Deploy and tailor fraud risk scoring systems for financial institutions across on-premise and cloud environments

Customer Success Software Engineer

Financial Crime

• Perform independent validation of AML and Financial Crime models
• Conduct threshold tuning and optimization of AML transaction monitoring scenarios
• Evaluate model methodologies, assumptions, data quality, and performance metrics
• Develop validation documentation, including validation reports, model assessments, playbooks, and runbooks
• Analyze large datasets to identify trends, anomalies, and model enhancement opportunities
• Assess risks associated with model design, implementation, and ongoing monitoring processes
• Provide recommendations for model improvements, process optimization, and risk mitigation
• Collaborate with Compliance, Financial Crime, Technology, and Business teams on model governance initiatives
• Monitor regulatory developments and industry trends related to AML, BSA, sanctions screening, and financial crime analytics
• Present findings, recommendations, and validation outcomes to stakeholders and senior management
• Support implementation and validation of new detection scenarios, models, and monitoring strategies
• Leverage data analytics and statistical techniques to evaluate model performance and suspicious activity detection capabilities
• Deliver regulatory-compliant model validations and assessments
• Improve AML model effectiveness through data-driven threshold tuning and optimization
• Identify emerging risks and recommend practical solutions
• Enhance model governance, documentation, and operational processes

Senior AML Transaction Monitoring

Data Engineer

• Develop, implement, and maintain production-grade data pipelines based on data science requirements
• Design and build scalable data flows for specific business use cases that can be integrated into the product
• Build and maintain machine learning data pipelines
• Create tools and frameworks that support data scientists and analytics teams in developing and optimizing innovative solutions
• Collaborate closely with Product, R&D, Data, and Analytics teams to enhance system functionality and performance
• Train customer data scientists and engineers on maintaining and enhancing data pipelines within the platform
• Travel domestically and internationally to support customers when required
• Build and manage strong technical relationships with customers and partners

Data Analyst

• Analyze and support Sanctions, Fraud, and AML models, including model tuning, optimization, and performance monitoring
• Apply model tuning methodologies and tools to improve model effectiveness and reduce false positives
• Analyze banking products, processes, systems, and transaction data to identify trends, patterns, and potential data or modeling issues
• Document model tuning methodologies, results, and optimization activities
• Prepare reports and presentations for senior management and regulatory stakeholders
• Perform quantitative analysis to evaluate model performance and identify opportunities for improvement
• Develop and analyze features and datasets to support statistical modeling and machine learning initiatives
• Collaborate with data scientists, model risk teams, technology teams, compliance professionals, and business stakeholders
• Work with large datasets and develop automation to improve data analysis and model-tuning processes
• Document and communicate analytical findings and recommendations to interdisciplinary teams
• Manage multiple priorities in a fast-paced environment with changing business requirements

Business Data Analyst

Business Development Rep

• Create and drive new sources of growth
• Lead business development, strategic partnerships, pricing and packaging, new offerings, AI commercialization, and go-to-market strategy
• Determine what sells, how it is positioned and priced, which partners can extend reach, and how new offerings are brought to market through Sales
• Drive measurable revenue impact through new PMC acquisition, upsell and cross-sell, increased deal size and attach rates, new revenue channels and partnerships, and expansion into new customer segments and markets
• Own pricing and packaging strategy, including tiers, bundles, commercial structures, and monetization models
• Translate new products, AI capabilities, and partner integrations into market-ready offerings with value propositions, pricing, target segments, and positioning
• Define commercialization of AI capabilities, including bundling, add-ons, and separate pricing
• Build commercial business cases for launching, bundling, repricing, expanding, or retiring offerings
• Equip Sales with positioning, packaging, competitive intelligence, pricing guidance, and commercial tools
• Develop and accelerate upsell and cross-sell strategies across the installed customer base
• Support strategic and complex opportunities involving new products, AI capabilities, partnerships, or non-standard commercial structures
• Ensure new offerings are adopted and sold by the Sales organization
• Analyze deal performance and customer adoption to improve conversion, average deal size, and expansion revenue
• Identify, develop, structure, negotiate, and close strategic partnerships, alliances, referral relationships, integrations, and channel opportunities
• Develop new routes to market and incremental revenue opportunities
• Evaluate partnerships based on strategic fit, customer value, revenue potential, economics, scalability, and long-term impact
• Own partnership opportunities from identification through relationship development, negotiation, agreement, launch, and ongoing execution
• Establish and maintain senior-level relationships across the property management and multifamily ecosystem
• Analyze the U.S. multifamily and property management market, customer segments, competitive dynamics, emerging technologies, and industry trends
• Identify new markets, regions, customer segments, and channels to expand
• Develop data-driven recommendations
• Identify emerging opportunities around AI, automation, payments, resident experience, property operations, and other technology trends
• Represent Matrix across industry associations, conferences, vendor networks, strategic accounts, and executive relationships
• Partner with VP Product, VP Sales, VP Growth, and Executive Leadership on commercialization, sales, growth, partnerships, and broader commercial strategy
• Define a pricing and packaging framework, improve deal size and attach rates, sign strategic partnerships, commercialize AI offerings, generate new revenue opportunities, and shape future market and channel strategy

Marketing Leader

Customer Success Software Engineer

Senior AML Transaction Monitoring

Data Engineer

Business Data Analyst

Director / VP of Business Development