About the Role
Description
Are you passionate about data, technology, and agribusiness?
We’re looking for a Mid-Level Data Scientist to join BIP Brasil and contribute to data-driven transformation projects in the agribusiness sector.
In this role, you’ll develop analytical models and solutions based on machine learning, geospatial data, satellite imagery, and other relevant information sources for agribusiness.
Projects may include agricultural monitoring, yield prediction, pattern recognition, territorial analysis, climate risk assessment, land use, market intelligence, operational efficiency, and decision support.
At BIP, you’ll work in a collaborative, multidisciplinary environment alongside professionals in data, technology, geospatial technologies, engineering, and business. We value curiosity, autonomy, continuous learning, and the ability to turn complex problems into pragmatic solutions.
Responsibilities
Develop and implement machine learning models and statistical techniques applied to agribusiness challenges.
Analyze geospatial, agronomic, climatic, operational, and market data.
Process satellite imagery, aerial photography, and other remote sensing data sources.
Build models for classification, segmentation, prediction, pattern detection, and insight generation.
Design and optimize geoprocessing algorithms to automate data analysis and processing workflows.
Use GIS tools for spatial analysis, interpretation, and visualization.
Integrate data from APIs, databases, files, geospatial platforms, and external sources.
Structure data preparation, validation, and enrichment processes.
Support the development of KPIs, dashboards, thematic maps, and analytical products.
Assess model quality, performance, and real-world applicability.
Document methodologies, assumptions, results, and limitations of analyses.
Prepare reports and presentations highlighting key findings and recommendations.
Collaborate with technology, data, business experts, and client teams.
Translate business needs into analytical hypotheses and data-driven solutions.
Support model deployment and evolution in production environments.
We seek professionals with experience in data science, geoprocessing, or spatial analysis, who are eager to understand agribusiness challenges and build solutions aligned with real client needs. Prior agribusiness experience is a plus but not required.
Prerequisites
Completed undergraduate degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Geography, Agronomy, Geoprocessing, or related fields. We also consider professionals from other backgrounds with relevant experience.
Requirements
Experience developing machine learning models or conducting statistical analyses.
Proficiency in Python or R for data handling, modeling, and analysis.
Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or equivalents.
Experience with geospatial data, spatial analysis, or geoprocessing.
Working knowledge of tools like QGIS, ArcGIS, or equivalent platforms.
SQL and relational database skills.
Ability to prepare, clean, validate, and analyze diverse datasets.
Strong communication skills to interpret results and convey conclusions clearly.
Knowledge of model evaluation and validation metrics.
Collaborative mindset and ability to work effectively in multidisciplinary teams.
Capacity to understand business problems and translate them into analytical approaches.
Preferred Skills (Not required to match all)
Processing and analysis of satellite imagery or aerial photography.
Remote sensing and vegetation indices.
Geospatial libraries: GeoPandas, Rasterio, GDAL, Shapely, or equivalents.
Google Earth Engine or other geospatial processing platforms.
Spatial databases (e.g., PostgreSQL/PostGIS).
Deep learning and computer vision techniques.
Frameworks: TensorFlow, PyTorch, or Keras.
Time series modeling, forecasting, and anomaly detection.
Cloud platforms: AWS, Google Cloud, or Microsoft Azure.
Distributed processing: Databricks, Spark, or similar.
Git and code versioning practices.
APIs, containerization, and model deployment fundamentals.
Visualization tools: Power BI, Tableau, Matplotlib, or Plotly.
MLOps practices, model monitoring, and lifecycle management.
Differentiators
Experience with agribusiness-related projects.
Knowledge of agricultural production, climate, soil, crops, field operations, or supply chains.
Experience with yield prediction models or crop monitoring.
Familiarity with meteorological, agronomic, or territorial data.
Experience analyzing land use and land cover.
Knowledge of spatial statistics and time series analysis.
Experience deploying models in enterprise environments.
Courses, specializations, or certifications in Data Science, AI, Geoprocessing, Remote Sensing, or Agribusiness.
Experiences
BENEFITS
Some of our benefits are flexible, allowing you to allocate them according to your needs, interests, and life stage:
All Points: Points program for flight tickets and accommodations.
Health Insurance
Dental Insurance
Life Insurance
Pet Assistance Program
Mobility Allowance: Includes fuel card and ride-hailing options (Uber, 99).
Flexible Reimbursement: For eyewear, vaccines, education, events, and more.
Meal and/or Food Vouchers
Additional Benefits:
Birthday off
Wellhub (Gympass membership)
Clube Alelo: Discounts at stores and pharmacies
180-day Maternity Leave
30-day Paternity Leave
Childcare Support in the baby’s first year
Transportation Voucher, based on project/area needs
Annual Bonus Program
Referral Commission for new client referrals
DEVELOPMENT PROGRAMS
At BIP, we think like entrepreneurs—planning three steps ahead to shape the future our clients want. To do this, we embrace lifelong learning and continuous growth.
As a Biper, you’ll be the protagonist of your career, supported by global and national development programs:
Global & National Training Hub: Access to up-to-date courses and content.
Flex Time: Dedicated weekly time for personal development.
Mentorship Programs: Guided by experienced leaders.
Biannual Performance Reviews
Feedback Culture: Regular 1:1s with leadership and team.
Personalized Development Plan aligned with your goals.
Darwin: Global program for young talent to build soft and hard skills.
Grounding: Global onboarding for early-career consultants.
Induction: International onboarding led by HR and business heads to introduce BIP’s culture, purpose, and global initiatives.
Spinnaker: Strategic leadership training for managers and senior managers to thrive in complex ecosystems.