Toast

• Collaborate with domain teams to implement a hub & spoke data architecture • Develop the core Analytics layer in our data warehouse that serves as the hub • Build an AI-ready semantic layer that is extendable across business domains • Partner with business stakeholders and our product team to understand their data analytics needs • Work closely with the data engineering team to ensure scalability across the platform • Provide technical mentorship and leadership to team members

• Design, own, and continuously improve the monthly agent release program. • Set and hold the platform-readiness bar. • Drive go-to-market coherence across LOBs. • Instrument launch health and build reporting that matters. • Operate with high judgment in ambiguous situations. • Establish the operating rhythms, governance structures, and cross-functional alignment mechanisms.

• Build and maintain reporting, dashboards, and analytics tools helping sales leaders and frontline teams understand performance, prioritize work, and identify growth opportunities. • Develop scalable analyses across sales execution, pipeline health, account prioritization, market coverage, territory performance, sales productivity, and growth planning. • Translate ambiguous business questions into structured approaches, insights, and recommendations for stakeholders. • Create decision support tools surfacing whitespace, high-priority accounts, coverage gaps, outreach penetration, funnel performance, and execution opportunities. • Conduct TAM, segment, and coverage analyses guiding leadership investments and scaling. • Own Retail’s territory analytics and operating infrastructure: design, account coverage, reporting, and maintenance. • Migrate manual workflows into scalable systems across Salesforce, Snowflake, and Sigma. • Develop territory visualization and mapping tools giving sales teams visibility into market coverage, prospect density, whitespace, and prioritization opportunities. • Partner with sales leadership to evaluate territory models, coverage, capacity, equity, and expansion opportunities. • Develop coverage strategies for new Retail segments and geographies as the business expands. • Build SQL/Python automations improving data quality and reducing manual work across data flows, scoring models, monitoring, and reporting. • Manage territory data loads, mapping configurations, and system updates with central operations and tech teams. • Build and maintain scalable enrichment workflows cleaning, classifying, and enhancing prospect and account data using LLMs. • Develop territory and account prioritization models using sales performance, volume potential, market characteristics, business attributes, and field capacity. • Own third-party market data strategy: vendor evaluation, procurement support, relationship management, and data quality oversight. • Build automated tools monitoring Rules of Engagement (ROE) exceptions, partnering with central governance to improve compliance workflows and automate resolutions. • Represent Retail’s territory data and infrastructure needs with cross-functional GTM partners across adjacent Business Technology, Data Infrastructure, and Finance. • Manage a roadmap of territory infrastructure enhancements based on impact and scalability. • Serve as Retail SME on territory operations, market coverage, account prioritization, and territory analytics.

• Stand up the Retail AI GTM Pod to surface, qualify, and scale AI applications • Serve as the production engine for ideas surfacing through the pod and field • Lead technical discovery to determine the most efficient path for problem statements • Maintain and execute against a technical scrum board, operating on defined sprint cycles • Coordinate integration efforts to map vertical AI outputs into core GTM platforms • Design and enforce security controls for Retail AI applications • Contribute to cross-functional AI coordination cadences connecting teams across Toast

• Own technical direction of the ML Platform — feature store, model hosting and serving, experimentation, training infrastructure — driving architectural decisions around scalability, reliability, latency, and cost • Lead design and delivery of large-scope platform initiatives from conception through production, coordinating across ML, data, and infrastructure teams • Identify and resolve systemic technical challenges: online/offline feature parity, model deployment friction, experimentation velocity, GPU utilization, cross-team dependencies • Set and maintain a high engineering quality bar through hands-on code contributions, design reviews, and mentorship of platform and ML-adjacent engineers • Partner with ML engineering, data science, product, and platform leadership to translate ML strategy into technical roadmaps • Define the paved paths ML teams use to ship models safely — from feature registration through canary rollout, monitoring, and rollback • Leverage AI-augmented development tools to increase development velocity and code quality

• Design, build, deploy, and maintain highly resilient and scalable systems that are critical to the success of Data at Toast • Develop and execute technical strategies to solve complex business challenges, leveraging data-driven decisions to prioritize impactful changes. • Build and maintain strong partnerships across lines of business, aligning technical solutions with strategic objectives. • Mentor and guide engineers, fostering a culture of continuous improvement, inclusivity, and engineering excellence. • Effectively communicate technical direction, guide teams through execution and drive organizational quality practices • Diagnose performance bottlenecks and implement optimizations • Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.

• Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives. • Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights. • Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy. • Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization. • Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise. • Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward. • Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.

• Perform analysis and build financial models to help inform data-driven capital markets decisions, gathering inputs from various stakeholders • Create and manage ongoing ABS-style reporting and audit cadences to uphold various types of financing relationships • Establish and maintain relationships with external capital teams to ensure compliance with contractual obligations • Help negotiate and execute on new capital commitments in the form of private credit arrangements • Collaborate with the Risk, R&D, Strategic Finance, Accounting, Product, Legal, Compliance, and Operations teams to evaluate and address capital markets impacts of new initiatives • Drive operational efficiencies across all capital markets functions • Build presentations to explain complex concepts, and deliver key information to a variety of audiences

• Apply a diverse set of expertise including data mining, statistical analysis and machine learning to deliver impactful, objective, and actionable data insights that enable informed business and product decisions • Collaborate with cross-functional teams, including sales, marketing, and product, to identify business opportunities and develop data-driven solutions that drive growth and engagement. • Partner with line of business teams and collaborate with product managers, engineers and data scientists to foster data-driven decisions that yield significant impacts • Able to effectively communicate analysis, insights and recommendations to high-level business partners in verbal, visual and written formats • Thrive in a dynamic and rapidly evolving environment

• Leverage your Toast Payroll product knowledge and project management skills to partner with restaurant owners during the Go-Live phase, and build out onboarding plans that will produce a high quality implementation and adoption experience. • The Onboarding Consultant is responsible for guiding customer through initial onboarding steps, including setting up client databases utilizing information from the previous payroll provider or data provided by the client • Create & lead an onboarding training plan for each customer on how to leverage the Toast product configured to their business and workflow • Manage several onboarding projects simultaneously, with a large book of business (60+ restaurants) in your backlog • Effectively collaborate with other Strategic Cuisines teams at Toast including but not limited to sales, onboarding, marketing, etc. • Ensure the customer’s transition to Toast Payroll goes smoothly and that you are available throughout the implementation to assist and guide the customer remotely • Assist and guide by providing post-live guidance, troubleshoot problems or follow-up training as needed by the customer • Assist in translation of customer-facing resources English to Mandarin as needed