Nlp Data Scientist - Remote Ml & Insights

Iv.Ai; Rosario; Remote; ARS 1,500,000 - 2,100,000; Full time

Job summary

Cargill is a leading global food and agricultural solutions company. This role sits at the heart of the data landscape, ensuring accuracy, security and value across the enterprise.

As Senior Consultant, Data Management and Governance you will develop and govern policies, standards and controls, drive data lifecycle activities, and collaborate with cross-functional teams to mitigate risk and enable insight.

Qualifications

• 4+ years of relevant work experience (Typically 5+ years).

Responsibilities

• Develops and governs data management and governance strategies aligned with organizational goals.
• Defines standards for data storage, data in transit, and data use.
• Develops, documents and governs detailed data standards to ensure consistency and quality.
• Ensures data accuracy and reliability across the data lifecycle via data quality audits.

Skills

Data governance

Data management

Data quality

Policy development

Data modeling

Job description

Senior Consultant, Data Management and Governance

Cargill is committed to providing food and agricultural solutions to nourish the world in a safe, responsible, and sustainable way. Sitting at the heart of the supply chain, we partner with farmers and customers to source, make and deliver products that are vital for living.
Our 155,000 team members innovate with purpose, providing customers with life's essentials so businesses can grow, communities prosper, and consumers live well. With over 160 years of experience as a family company, we look ahead while remaining true to our values. We put people first. We reach higher. We do the right thing-today and for generations to come.

Job Purpose and Impact

The Senior Professional, Data Management & Governance job ensures the accuracy, security and effective use of the organization's complex data. With minimal supervision, this subject matter authority develops, implements and governs policies and practices to ensure compliance with regulations while improving the value of data.

Key Accountabilities

• STRATEGIC PLANNING: Serves as a domain expert and contributes to developing, deploying and maintaining data management and governance strategies aligned with organizational goals.


• DATA STORAGE, INTEGRATION & CONSUMPTION: Develops, governs and monitors the implementation of standards for data storage, data in transit and data use in both raw and insight formats, and defines the business risk for non-compliance.


• DATA STANDARDS: Develops, documents and governs detailed data standards to ensure consistency and quality across data domains, and that policies are followed.


• DATA QUALITY: Ensures the accuracy, consistency and reliability of data throughout its lifecycle by setting data quality standards, supervising data quality metrics and implementing corrective processes while conducting data quality audits as needed to ensure data standards are met, and works across organizational boundaries to address process changes, educational opportunities and organizational accountability.


• POLICY DEVELOPMENT & GOVERNANCE: Leads the development and operational alignment of data governance policies, providing expertise of given domain or capability.


• DATA OPERATIONS & STEWARDSHIP: Serves as a domain authority to provide operational improvements to reduce data quality defects, improve efficiency and speed while maintaining compliance to regulations and policies.


• DATA LIFECYCLE MANAGEMENT: Handles complex data from initiation to decommissioning through the lifecycle to ensure compliance with policies and regulations and serves as a subject matter authority to define opportunities for improvement, risk areas and driving a backlog of maturity advancements for consideration.


• COMPLIANCE & RISK MANAGEMENT: Develops, improves, implements data governance, risk and compliance processes and controls to mitigate risk and align with applicable laws and regulations.


• DATA LITERACY & TRAINING: Develops and deploys training programs to improve organizational literacy, compliance to data standards and policies and increased understanding of accountability for data responsibilities.


• DATA MODELING: Informs the visual representation of a system's data and its relationships to help understand and prioritize the data structure.

Qualifications

• Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.