Director of Data

At Corsearch, we are dedicated to creating a world where consumers can trust the choices they make.

As a global leader in Trademark and Brand Protection, we partner with businesses to safeguard their most valuable assets in an increasingly complex digital environment.

Our comprehensive solutions, powered by AI-driven data and deep analytics, enable brands to establish, monitor, and protect their presence against infringement and counterfeiting.

Why Choose Corsearch?

• Innovative Solutions: We combine cutting-edge technology with expert judgment to deliver market-leading services in trademark clearance, brand protection, and anti-counterfeiting.
• Global Impact: Trusted by over 5,000 customers worldwide, including 73 of Fortune's Top 100 companies, our work has a meaningful impact on businesses and consumers alike.
• Collaborative Culture: With a team of over 1,900 professionals across multiple global offices, you'll be joining an inclusive environment where diverse perspectives thrive.
• Mission-Driven Purpose: Our commitment to protecting consumers and their trust in brands drives everything we do, making Corsearch a force for good in the world.

✅The Role

We are seeking a Director of Data & Analytics to lead our data strategy and execution across the company.

This role will oversee data science, analytics, and reporting functions, driving innovation in product intelligence, customer insights, and operational efficiency. You'll serve as a strategic partner to leaders across the organization, defining the analytics roadmap and promoting data driven decision making across the organization.

The ideal candidate is both a strategic leader and a hands-on practitioner who thrives in high-growth SaaS environments.

✅Responsibilities and Duties

Leadership & Strategy

• Define and execute the company’s data and analytics strategy in alignment with business and product goals.
• Establish strategic processes that uncover root cause issues and define clear pathways to resolution.
• Build, scale, and mentor a high performing team of data scientists, analysts, and machine learning engineers.
• Partner with executives and functional leaders to ensure data driven decision making across the organization.
• Champion data-driven decision-making across the organization

Data Analytics & Business Insights

• Lead the development of core company analytics including SaaS KPIs (ARR, churn, CAC, LTV, NRR, etc.).
• Build executive dashboards and self-service analytics to empower teams across product, marketing, sales, finance, and customer success.
• Partner with GTM teams to optimize pipeline, conversion, and expansion through analytics driven insights.
• Conduct cohort, funnel, and retention analyses to identify customer behavior patterns and growth opportunities.
• Translate complex datasets into clear narratives and recommendations for senior leadership

Customer Reporting & Insights

• Partner with the GTM teams to execute on customer facing analytics and reporting features
• Partner with product management to deliver scalable, intuitive dashboards and reports that add customer value and increase stickiness.
• Collaborate with customer success to provide insights that strengthen adoption, retention, and expansion.
• Partner with Product teams to share customer insights and sentiment that inform and shape the roadmap.

Data Infrastructure & Collaboration

• Partner with data engineering to ensure scalable, reliable pipelines and a modern data platform.
• Champion best practices in data governance, accessibility, and quality across all analytics and science initiatives.

✅Essential

• 10+ years in data analysis, with at least good experience in a leadership role.
• Proven track record leading data teams in a SaaS or tech-driven company.
• Experience collaborating with product and engineering teams on embedded data science and reporting solutions.
• Demonstrated success building or scaling customer-facing reporting or analytics capabilities.

✅Technical Skills

• Strong expertise in statistical modeling, machine learning, and experimentation.
• Proficiency in Python or R, SQL, and data science libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Familiarity