VP, Data Science

Axial Search; United States; On-site; USD 180,000 - 350,000; Full time

Job summary

Axial Search in the United States is seeking a senior data science leader to own the end-to-end strategy and roadmap, partnering with product, engineering, and business leadership to identify high-impact use cases and prioritize delivery.

The role centers on building a high-performing data science team, deploying machine learning models to production, translating insights for executives, and establishing governance with scalable pipelines while balancing innovation with delivery timelines.

Qualifications

• 7+ years of hands-on experience in data science, machine learning, or quantitative analysis, with demonstrated expertise in statistical modeling and ML techniques.
• 3+ years leading and managing data science or analytics teams, with a track record of growing talent and shipping impactful work.
• Proven ability to take models from concept to production, including experience with model deployment, monitoring, and iteration in real-world settings.
• Strong communicator who can translate technical complexity for non-technical stakeholders and align data science work with business objectives.
• Experience working cross-functionally with product, engineering, and business teams to scope and prioritize data science initiatives.
• Fluency in Python or R and familiarity with modern ML tools and infrastructure (cloud platforms, containerization, workflow orchestration).

Responsibilities

• Own the end-to-end data science strategy and roadmap, partnering with product, engineering, and business leadership to identify high-impact use cases and prioritize delivery
• Build and lead a high-performing data science team, hiring talent, setting technical standards, and fostering a culture of rigor and experimentation
• Drive the development and deployment of machine learning models that solve real business problems, from ideation through production and monitoring
• Translate complex analytical findings into clear insights and recommendations for executive stakeholders, communicating trade-offs and business impact
• Establish best practices for data governance, model validation, and measurement frameworks across the organization
• Partner with data engineering and infrastructure teams to ensure scalable pipelines, reproducible workflows, and reliable model serving
• Evaluate emerging techniques and tools in machine learning and AI, balancing innovation with pragmatic delivery timelines

Skills

Data science

Machine learning

Quantitative analysis

Statistical modeling

Model deployment

Monitoring

Cross-functional collaboration

Python

R

Cloud platforms

Containerization

Workflow orchestration

Tools

Cloud platforms

Containerization

Workflow orchestration

Job description

Axial Search is a specialist executive search firm built for one kind of hire: leaders who help organizations navigate AI transformation.

What The Market Looks Like

We've tracked 100+ senior-level data science postings in the United States over the last six months, with concentrated hiring in California, New York, and Washington. Organizations across technology, financial services, professional services, and manufacturing are building or scaling data science teams, and compensation for experienced VPs typically ranges from $180K to $350K. The strongest candidates in this market bring deep technical credibility in machine learning and statistical modeling, proven ability to lead and develop data science teams, experience translating complex analyses into business strategy, and a track record shipping production systems that drive measurable ROI.

Job Responsibilities

• Own the end-to-end data science strategy and roadmap, partnering with product, engineering, and business leadership to identify high-impact use cases and prioritize delivery
• Build and lead a high-performing data science team, hiring talent, setting technical standards, and fostering a culture of rigor and experimentation
• Drive the development and deployment of machine learning models that solve real business problems, from ideation through production and monitoring
• Translate complex analytical findings into clear insights and recommendations for executive stakeholders, communicating trade-offs and business impact
• Establish best practices for data governance, model validation, and measurement frameworks across the organization
• Partner with data engineering and infrastructure teams to ensure scalable pipelines, reproducible workflows, and reliable model serving
• Evaluate emerging techniques and tools in machine learning and AI, balancing innovation with pragmatic delivery timelines

Candidate Requirements

• 7+ years of hands-on experience in data science, machine learning, or quantitative analysis, with demonstrated expertise in statistical modeling and ML techniques
• 3+ years leading and managing data science or analytics teams, with a track record of growing talent and shipping impactful work
• Proven ability to take models from concept to production, including experience with model deployment, monitoring, and iteration in real-world settings
• Strong communicator who can translate technical complexity for non-technical stakeholders and align data science work with business objectives
• Experience working cross-functionally with product, engineering, and business teams to scope and prioritize data science initiatives
• Fluency in Python or R and familiarity with modern ML tools and infrastructure (cloud platforms, containerization, workflow orchestration)