Job Description:

We are re-imagining agricultural insurance with the power of Public Cloud, GIS, Remote-sensing and cutting-edge AI-based algorithms to assess, model and price insurance risks for farmers adequately. We are taking the latest advances in Mobile, Geospatial technologies and the web to empower the next generation of agricultural insurance.

We are looking for a Chief Data Officer (CDO) who is responsible for overseeing an organizations data strategy, ensuring data quality, governance, and utilization to drive business decisions and innovation. This role will play a pivotal role in development of a data-driven culture, oversees the integration of advanced analytics, and ensures the integrity, privacy, and security of companys data. This senior leadership role requires a strategic thinker with deep technical knowledge, business acumen, and a focus on integrating innovative and varied data sources to enhance decision-making across the organization.

The CDO will partner with key business stakeholders to ensure that the organization can leverage its data assets effectively for competitive advantage, operational efficiency, faster / accurate decision making and regulatory compliance.

Key Responsibilities:

1. Data Strategy and Management:

- Design and implement comprehensive data strategy that includes integration of in-house / external data sources, GIS / satellite imagery and aligns with broader organizational goals.

- Develop a scalable and robust data architecture to facilitate data integration, storage, and access.

- Assess the current organizational data maturity and define the roadmap to identify and implement data catalog, data cleansing, data management and data analytics tools.

2. Data Security and Governance:

- Establish and enforce data governance, security standards, policies, and procedures to ensure data quality, privacy, and compliance.

- Designate data owners and stewards for different departments to ensure that data is managed properly, with clear accountability for data quality, access, and usage.

- Define and implement security measures, ensuring that only authorized personnel can access sensitive data, and that access is granted based on business needs and audited.

3. Data Analytics and Insights:

- Implement predictive analytics and AI / ML models to improve customer segmentation, pricing optimization, claims / underwriting decision making and risk management.

- Provide actionable insights to business leaders, underwriters, claims managers, and customer experience teams to improve operational efficiency and customer satisfaction.

- Enhance the organization's data visualization capabilities, ensuring that key performance indicators (KPIs) and insights are easily accessible for decision-makers across the business.

4. Leadership and Collaboration:

- Lead and mentor the data science, analytics, and data management teams, fostering a data-driven culture throughout the organization.

- Collaborate with executive leadership (CEO, COO, CFO, etc.) to ensure data strategies are aligned with business goals.

- Build and nurture relationships with business units (e.g., actuarial, underwriting, claims, marketing, and finance) to ensure alignment on data priorities and business objectives.

5. Innovation and Digital Transformation:

- Stay abreast of the latest developments in data technologies, AI, machine learning, and insurtech innovations, applying these advancements to continuously improve the company's data infrastructure and analytics capabilities.

- Drive the adoption of cloud-based data solutions and automation tools to streamline claims processing, underwriting decisions, and other key operational processes.

- Lead efforts to integrate external data sources (e.g., third-party data, IoT, telematics) into the organization's workflows for better risk modeling and customer insights.