Data Science Vice President

Synchro; Austin (TX); On-site; USD 250,000 - 360,000; Full time

Job summary

Synchro seeks a Vice President of Data Science to drive strategy and execution for applied machine learning and AI, scaling the team and delivering production-ready solutions that boost pricing, marketing efficiency, conversion, and customer experience.

Reporting to the CTO, this leader will define the long-term vision, build the data science organization, and align with senior engineering and data leaders to translate business priorities into scalable, measurable AI initiatives.

Qualifications

• 10+ years of experience in data science and machine learning, including 5+ years leading and scaling teams in high-growth technology, fintech, or digital marketplace environments.
• Strong foundation in predictive modeling, supervised and unsupervised machine learning, causal inference, and experimentation.
• Proficiency in Python, modern data platforms such as Snowflake or Databricks, and production MLOps.
• Experience implementing modern AI technologies, including LLM reasoning architectures and automated evaluation pipelines.
• Commercial experience in performance marketing, digital acquisition, recommendation engines, or insurance and risk pricing.

Responsibilities

• Define short- and long-term data science strategies tied to revenue growth, customer lifetime value, and operating margin
• Partner with Commercial, Product, Growth, and Marketing leaders on lead qualification, attribution, and customer acquisition optimization
• Lead predictive and generative models from prototype through production deployment and ongoing validation
• Expand capabilities in dynamic pricing, conversion optimization, risk modeling, and marketplace matching
• Implement modern AI solutions, including LLM-based systems, workflow automation, and agentic tools where they deliver measurable value
• Partner with Data leadership on training data, feature stores, and warehouse architecture
• Collaborate with Engineering to build reliable MLOps pipelines and integrate scalable models into customer-facing products

Skills

Data science

Leadership

Python

ML & AI

MLOps

LLM architectures

Experimentation

Pricing optimization

Marketing analytics

Tools

Snowflake

Databricks

Job description

Our client is seeking a Vice President of Data Science to turn data science into a key driver of business growth. 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 Responsibilities

Strategy & Business Impact

• Define short- and long-term data science strategies tied to revenue growth, customer lifetime value, and operating margin
• Partner with Commercial, Product, Growth, and Marketing leaders on lead qualification, attribution, and customer acquisition optimization
• Lead predictive and generative models from prototype through production deployment and ongoing validation
• Expand capabilities in dynamic pricing, conversion optimization, risk modeling, and marketplace matching
• Implement modern AI solutions, including LLM-based systems, workflow automation, and agentic tools where they deliver measurable value

Cross-Functional Execution

• Partner with Data leadership on training data, feature stores, and warehouse architecture
• Collaborate with Engineering to build reliable MLOps pipelines and integrate scalable models into customer-facing products

What Success Looks Like

• First 90 days: Assess existing models and initiatives, establish a six-month roadmap, and align stakeholders on priority opportunities
• First 180 days: Launch models that demonstrate measurable conversion or revenue gains, standardize experimentation, and begin scaling the team
• First year: Establish a high-velocity data science organization supporting personalization, pricing recommendations, and marketing efficiency

Qualifications

• 10+ years of experience in data science and machine learning, including 5+ years leading and scaling teams in high-growth technology, fintech, or digital marketplace environments
• Strong foundation in predictive modeling, supervised and unsupervised machine learning, causal inference, and experimentation
• Proficiency in Python, modern data platforms such as Snowflake or Databricks, and production MLOps
• Experience implementing modern AI technologies, including LLM reasoning architectures and automated evaluation pipelines
• Commercial experience in performance marketing, digital acquisition, recommendation engines, or insurance and risk pricing
• Strong executive communication skills, with the ability to explain technical concepts to non-technical stakeholders
• Competitive compensation and equity
• Medical, dental, vision, and disability coverage
• Health savings account contribution
• 401(k) with employer match
• Flexible paid time off and paid parental leave
• Sabbatical program for eligible employees
• Wellness and pet benefits, plus fertility support