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Odimar Almeida

@odimaralmeida

Message

I lead seed production data science, turning biological data into automated, AI-driven decisions.

Brazil

Message

What I'm looking for

I'm looking to scale digital transformation in the seed industry through data science, AI, automation, and collaborative global initiatives that improve productivity and food security.

I lead Data Science for Seed Production Research at Syngenta, developing automation and visualization platforms while representing Brazil in global data governance and system-harmonization projects.

I direct AI initiatives using drones, mobile devices, and X-ray imaging to support field and laboratory decisions. I established an AWS Redshift database for automated stakeholder reporting and introduced logistic, multinomial, and ordinal regression models to strengthen inbred-line characterization and genetic prediction.

My background combines a PhD in Genetics and Breeding with research in genomic association, digital phenotyping, sugarcane disease resistance, and plant genetic diversity. I use R, Python, SQL, computer vision, and predictive modeling to scale digital transformation in the seed industry and improve productivity.

Experience

Work history, roles, and key accomplishments

Current

SPR Data Science Lead

Current

Syngenta

Aug 2022 - Present (4 years 1 month)

Lead the Data Science area for SPR, coordinating the development of platforms for process automation and data visualization.

Serve as the Brazilian Representative for global projects focused on data governance and system harmonization.

Direct AI projects utilizing drones, mobile devices, and X-ray imaging for field and lab decision support.

Established an AWS Redshift database to automate repor

R Python SQL AWS RedShift Computer Vision AI Statistical Modeling Data Governance Project Management

Scientific Researcher

Federal University of Viçosa

Mar 2018 - Jul 2023 (5 years 4 months)

Acting area: Genome Association and Digital Phenotyping on Sugarcane Breeding

Tasks:
- Planning of trials for assessment of sugarcane genotypes for resistance to sugarcane smut disease;
- Management of teams for seedling preparation;
- Spores collect on infested fields;
- Development and validation of protocol for spores viability test;
- Conduction of trials for disease reaction in greenhouse;
-

Data Scientist

Syngenta

Dec 2021 - Aug 2022 (8 months)

Standardized data transfer processes to official platforms and developed the first interactive RShiny dashboards for the department.

Scaled digital solutions internationally by supporting the integration of RShiny visualizations for the Argentina team.

Marketing Coordinator

GenMelhor - UFV

Jan 2019 - Dec 2020 (1 year 11 months)

Simulated corporate team environments, leading the "GenetiCast" podcast and reducing operational costs for event management.

Scientific Researcher

UENF - State University of Northern Fluminense

Apr 2015 - Feb 2017 (1 year 10 months)

Acting area: Genetic Diversity of Interspecific Population of Psidium sp.

Tasks:
- Crossing between plants of Psidium genera;
- Conduction of segregant populations in greenhouse;
- Extraction, conduction and inoculation of root-not nematode;
- Characterization based on morfoagronomical markers;
- Genetic diversity study for quantitative and qualitative traits.

Softwares used:
- Excel;
- Word;
-

Intern

Empresa Brasileira de Pesquisa Agropecuária - Embrapa

Feb 2011 - Jul 2014 (3 years 5 months)

Acting area: Breeding of Native Fruits form Amazon

Tasks:
- Assessment of yield and disease resistance trials on cupuaçu crop;
- Research data manipulation;
- Experimental data analysis;
- Design of graphic and charts;
- Writting of reports and manuscripts for scientific events.

Softwares used:
- Excel
- Word
- GENES
- Minitab

Education

Degrees, certifications, and relevant coursework

Universidade Federal de Viçosa

Doctor of Philosophy, Genetics and Breeding

2018 - 2023

Doctoral research focused on genomic wide association studies (GWAS) in sugarcane for disease resistance, applying machine learning and CNNs for pathogen identification.