[ZH-64] Data Science Data Science Senior Data Scientist (Python) (Remote)

Biome Makers; Galapagar; A distancia; EUR 40.000 - 70.000; Jornada completa

Descripción de la vacante

Una empresa de AgTech está buscando un/a Senior Data Scientist para desarrollar modelos complejos utilizando datos microbiomáticos y ambientales. El/la candidato/a ideal tiene un PhD en un campo relacionado y 4+ años de experiencia en ciencia de datos. Se valoran habilidades en Python, R, y experiencia con herramientas de CI/CD, así como un ambiente de trabajo remoto. Oportunidades de desarrollo profesional y educación están disponibles para todos los solicitantes calificados.

Servicios

Oportunidades de desarrollo profesional

Trabajo remoto

Formación

• Fuerte conocimiento en inferencia estadística y algoritmos de machine learning.
• Experiencia práctica en bases de datos relacionales y consultas SQL.
• Experiencia en el desarrollo de flujos de trabajo reproducibles.

Responsabilidades

• Diseñar e implementar modelos estadísticos y de machine learning para analizar datos ambientales y microbiomáticos.
• Integrar datos GIS en modelos predictivos.
• Mantener un código bien documentado y modular con control de versiones.

Conocimientos

Programación en Python

Análisis de datos biológicos

Modelos de machine learning

Control de versiones (Git)

Educación

PhD en bioinformática, estadística o campo relacionado

Herramientas

Jupyter

AWS

GIS

Descripción del empleo

Biome Makers is a global AgTech company on a mission to restore soil health! Founded in California’s Silicon Valley in 2015, we are setting the standard in soil health with BeCrop technology.

We integrate soil microbiology into agricultural decision-making to optimize farming practices and reverse soil degradation. With labs across the globe, customers on 4 continents, and impacting over 1 million acres, we are revitalizing soil functionality and sustainability worldwide.

We are seeking a Senior Data Scientist with strong programming skills, advanced knowledge of statistical and machine learning modeling, and experience working with biological and environmental datasets, including microbiome data. You will design and implement robust, reproducible analytical solutions, integrating geospatial (GIS) data and CI / CD tools such as Jenkins into modeling pipelines.

Location

Spain (remote)

Responsibilities

• Design and implement statistical and machine learning models for complex biological and environmental data, including microbiome datasets.
• Analyze microbiome and spatial data using reproducible, automated workflows (e.g., RMarkdown, Jupyter).
• Integrate GIS data (spatial layers, raster / vector models) into predictive and inferential models.
• Maintain well-documented, modular code using version control (Git), following best practices in software engineering and reproducibility.
• Set up and manage automated workflows using CI / CD tools like Jenkins to streamline testing, deployment, and reproducibility.

Qualifications

• PhD (or equivalent) in bioinformatics, statistics, computer science, environmental science, or a related field.
• Approximately 4+ years of experience as a Data Scientist or Statistician (industry or academia).
• Hands-on experience with biological count or compositional data.
• Advanced knowledge of statistical inference and machine learning algorithms (supervised and unsupervised).
• Strong programming skills in Python and R.
• Proficiency with version control systems (Git).
• Experience with CI / CD tools such as Jenkins.
• Experience developing reproducible data workflows (e.g., RMarkdown, Jupyter).
• Familiarity with relational databases and SQL querying.
• Practical experience with GIS tools and R libraries.

Additional Skills

• Experience with cloud platforms (e.g., AWS).
• Comfort working in Unix / Linux environments.
• Exposure to DevOps practices and tools (e.g., containerization, monitoring).
• Background in soil or environmental / agri-food applications.
• Remote work environment
• Professional development and education opportunities

Our team spans soil science, agriculture, genetics, biotechnology, computer science, and more, promoting sustainable agriculture worldwide. We value diversity and are an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability, or veteran status.

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