VP of Data, Analytics and AI

Posted 2 days agoViewed

💎 Seniority level: Vp, 10+ years

📍 Location: United States

🔍 Industry: Computer Software

🏢 Company: Worth AI👥 11-50💰 $12,000,000 Seed over 1 year agoArtificial Intelligence (AI)Business Intelligence Risk Management FinTech

🗣️ Languages: English

⏳ Experience: 10+ years

Requirements:

10+ years in data leadership roles, including at least 5 years leading large-scale data initiatives in fast-paced, data-driven environments.

Experience with risk technology or credit modeling in enterprise contexts is a strong plus.

Proven expertise in monetizing data assets and building governance structures at scale.

Strong understanding of data platforms (e.g., Snowflake, Databricks), cloud architecture, data pipelines, and modern analytics tooling.

Demonstrated ability to lead multidisciplinary teams, craft vision and strategy, and drive tactical execution.

Outstanding communication and stakeholder management skills, with the ability to convey complex data concepts to technical and non-technical audiences.

Deep experience in data science, machine learning, AI, and credit or risk modeling.

Strong problem-solving and data interpretation skills with a focus on delivering results.

Responsibilities:

Lead a growing team of approximately five data professionals across engineering, analytics, data science, and governance.

Be a hands-on leader who actively engages in code reviews, model reviews, and technical deep dives to stay connected to the day-to-day realities of engineering and data science work.

Set a high technical bar while mentoring and developing team members, fostering a culture of innovation, ownership, and collaboration.

Lead the end-to-end strategy for acquiring first-party, second-party, and third-party data sources aligned to business priorities.

Evaluate and negotiate data licensing agreements and strategic partnerships to grow our data asset portfolio.

Design robust, scalable, and compliant ingestion pipelines for efficient data integration and enrichment.

Utilize data science, machine learning, and AI techniques to design, test, and deploy advanced risk, fraud, and credit scoring models.

Identify, define, and execute on opportunities to monetize data assets—both directly and through data-enabled products and services.

Partner closely with Product, Sales, Marketing, Strategy, and Customer Success to integrate data insights into go-to-market initiatives and client-facing solutions.

Translate data into actionable business intelligence that informs strategy and drives measurable business growth.

Build scalable, repeatable processes for data management—spanning integration, transformation, quality assurance, and delivery.

Champion the adoption of modern data platforms and tools (e.g., Snowflake, Databricks, dbt) to support real-time decision-making and automation.

Develop and lead a high-performing data team across engineering, analytics, data science, and governance, fostering a culture of innovation, collaboration, and accountability.

Own and evolve data governance frameworks to ensure integrity, quality, security, and compliance with global regulations (e.g., GDPR, CCPA).

Establish clear data ownership and stewardship models, along with standardized policies for access, lineage, and privacy.

Proactively manage data risk and embed ethical practices into all aspects of data use and monetization.

Partner with engineering, product, finance, and other internal teams to ensure alignment on data initiatives.

Serve as the internal advocate for data as a strategic asset, ensuring organizational alignment around data value and strategy.

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