Data Science Vice President
Synchro · Austin, Texas Metropolitan Area
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This leader will define the strategy for applied machine learning and AI, scale the existing team, and deliver production-ready solutions that improve pricing, marketing efficiency, conversion, and customer experience.Reporting to the CTO and partnering with executive AI leadership, the VP of Data Science will define the long-term machine learning and AI vision, develop the data science team, and collaborate with senior Engineering and Data leaders to turn commercial and product priorities into scalable, measurable solutions.Key ResponsibilitiesStrategy & Business ImpactDefine short- and long-term data science strategies tied to revenue growth, customer lifetime value, and operating marginPartner with Commercial, Product, Growth, and Marketing leaders on lead qualification, attribution, and customer acquisition optimizationMachine Learning & AI DeliveryLead predictive and generative models from prototype through production deployment and ongoing validationExpand capabilities in dynamic pricing, conversion optimization, risk modeling, and marketplace matchingImplement modern AI solutions, including LLM-based systems, workflow automation, and agentic tools where they deliver measurable valueCross-Functional ExecutionPartner with Data leadership on training data, feature stores, and warehouse architectureCollaborate with Engineering to build reliable MLOps pipelines and integrate scalable models into customer-facing productsWhat Success Looks LikeFirst 90 days: Assess existing models and initiatives, establish a six-month roadmap, and align stakeholders on priority opportunitiesFirst 180 days: Launch models that demonstrate measurable conversion or revenue gains, standardize experimentation, and begin scaling the teamFirst year: Establish a high-velocity data science organization supporting personalization, pricing recommendations, and marketing efficiencyQualifications10+ years of experience in data science and machine learning, including 5+ years leading and scaling teams in high-growth technology, fintech, or digital marketplace environmentsStrong foundation in predictive modeling, supervised and unsupervised machine learning, causal inference, and experimentationProficiency in Python, modern data platforms such as Snowflake or Databricks, and production MLOpsExperience implementing modern AI technologies, including LLM reasoning architectures and automated evaluation pipelinesCommercial experience in performance marketing, digital acquisition, recommendation engines, or insurance and risk pricingStrong executive communication skills, with the ability to explain technical concepts to non-technical stakeholdersBenefits & PerksCompetitive compensation and equityMedical, dental, vision, and disability coverageHealth savings account contribution401(k) with employer matchFlexible paid time off and paid parental leaveSabbatical program for eligible employeesWellness and pet benefits, plus fertility support