Bovine Genetic Improvement Analyst - Technology

Description

Job Summary: Professional to perform genetic and zootechnical data analysis, herd monitoring, and support for genetic selection programs. Key Highlights: 1. Genetic and zootechnical data analysis and integration 2. Cattle herd monitoring and report generation 3. Support for genetic selection programs and innovation **OPEN POSITION – GENETIC IMPROVEMENT ANALYST (IT)** **Location:** Uberaba – MG **Sector:** Livestock **Contract Type:** CLT **Working Hours:** Monday to Friday \| 7:30 AM to 11:30 AM / 1:30 PM to 5:30 PM **Career Development Plan:** Yes **Salary:** R$ 3\.958,11 **Benefits:** * Meal/food allowance: R$ 675.00 * Health insurance * Dental insurance * Life insurance * Transportation voucher * Wellhub * Partnerships (clubs and pharmacies) * Special assistance **Education (Technology Field):** Information Systems, Computer Science, Software Engineering, Computer Engineering, Systems Analysis and Development, or related fields. **Main Responsibilities:** * Genetic and zootechnical data analysis * Monitoring of cattle herd data * Report and dashboard generation * Genomic data integration and analysis * Support for genetic selection programs **Desirable Qualifications:** Experience in data analysis, administrative routines, attention to detail, and teamwork. **Main Responsibilities:** * Genetic and zootechnical data analysis * Monitoring of cattle herd data * Report and dashboard generation * Genomic data integration and analysis * Support for genetic selection programs Data collection and organization * Collect zootechnical data (weight, age, milk production, fertility). * Integrate data from multiple sources (farms, laboratories, IoT sensors). * Ensure quality and consistency of collected data. * Structure databases to store genetic information. Genetic and statistical analysis * Analyze genetic data (e.g., SNP markers and pedigrees). * Apply statistical models to estimate genetic values (DEP/EBV). * Develop algorithms for selecting superior animals. * Evaluate heritability of productive traits. * Conduct predictive analyses for future animal performance. Development and technology * Create interactive dashboards for herd monitoring. * Develop scripts (Python, R) to automate analyses. * Implement genomic data processing pipelines. * Apply machine learning for genetic prediction. * Integrate agricultural management systems with analytical platforms. Decision-making and strategy * Support genetic crossbreeding decisions. * Identify top-performing sires and dams. * Generate technical reports for veterinarians and animal scientists. * Monitor herd performance indicators. Innovation and research * Participate in genetic improvement research projects. * Evaluate emerging technologies (genomics, artificial intelligence applied to agriculture).