Mid-level Data Scientist – Image Geoprocessing, GIS

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BIP Brasil

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2003

📦 Logistics

📣 Marketing

🏭 Manufacturing

Logistics • Marketing • Manufacturing

BIP Brasil is an international consulting firm that drives significant transformation through a personalized approach, fostering a maker culture and pioneering spirit in a constantly changing environment. They support major players in various sectors with transformation projects, and their extensive expertise includes risk management, technology implementation, and supply chain innovations across multiple industries.

📋 Description

• 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 photographs, and other remote sensing data sources • Build models for classification, segmentation, forecasting, pattern detection, and insight generation • Create and optimize geoprocessing algorithms to automate analyses and data workflows • Use GIS tools for analysis, interpretation, and visualization of spatial information • Integrate data from APIs, databases, files, geospatial platforms, and external sources • Structure processes for data preparation, validation, and enrichment • Support the development of KPIs, dashboards, thematic maps, and analytical products • Assess the quality, performance, and applicability of developed models • Document methodologies, assumptions, results, and limitations of analyses • Prepare reports and presentations with key results and recommendations • Collaborate with technology, data, business specialists, and client teams • Translate business needs into analytical hypotheses and data-driven solutions • Support the deployment and iteration of models in production environments

🎯 Requirements

• Bachelor's degree (or higher) in Data Science, Computer Science, Statistics, Mathematics, Engineering, Geography, Agronomy, Geoprocessing, or related fields • Candidates from other backgrounds with relevant experience will also be considered • Experience developing machine learning models or performing statistical analyses • Proficiency in Python or R for data processing, modeling, and analysis • Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or equivalents • Experience with geospatial data, spatial analysis, or geoprocessing • Familiarity with tools like QGIS, ArcGIS, or equivalent platforms • Knowledge of SQL and relational databases • Ability to prepare, clean, validate, and analyze diverse datasets • Ability to interpret results and communicate conclusions clearly • Knowledge of model evaluation and validation metrics • Comfortable working collaboratively in multidisciplinary teams • Ability to understand business problems and translate them into analytical approaches • Experience processing and analyzing satellite imagery or aerial photographs • Experience with remote sensing and vegetation indices • Geospatial libraries such as GeoPandas, Rasterio, GDAL, Shapely, or equivalents • Google Earth Engine or other geospatial processing platforms • Spatial databases such as PostgreSQL/PostGIS • Deep learning and computer vision techniques • Frameworks like TensorFlow, PyTorch, or Keras • Time series models, forecasting, and anomaly detection • Cloud computing platforms such as AWS, Google Cloud, or Microsoft Azure • Databricks, Spark, or other distributed processing technologies • Git and code versioning practices • APIs, containers, and fundamentals of model deployment • Visualization tools such as Power BI, Tableau, Matplotlib, or Plotly • MLOps practices, monitoring, and model lifecycle management • Experience with agribusiness-related projects • Knowledge of agricultural production, climate, soils, crops, farm operations, or supply chains • Experience with crop yield forecasting models or field monitoring • Knowledge of meteorological, agronomic, or territorial data • Experience with land use and land cover analysis • Knowledge of spatial statistics and time series • Experience deploying models in corporate production environments • Courses, specializations, or certifications in Data Science, Artificial Intelligence, Geoprocessing, Remote Sensing, or Agribusiness

🏖️ Benefits

• All Points (points program for flights and accommodations) • Medical insurance • Dental insurance • Life insurance • Pet care plan • Mobility support (including fuel allowance and rideshare options such as Uber, 99) • Reimbursement Flex (glasses, vaccines, education, events, and other expenses) • Meal voucher and/or food allowance • Birthday off • Wellhub (Gympass) • Alelo Club with various store and pharmacy discounts • 180-day maternity leave • 30-day paternity leave • Childcare assistance during the child's first year • Transportation allowance according to project or area needs • Annual bonus program • Commission for referral of new clients • A global TRAINING and DEVELOPMENT center with up-to-date market content and courses • Flex Time – a weekly period dedicated to your development • Mentorship programs with experienced leaders • Semi-annual performance reviews • Culture of feedback and recurring 1:1s with your manager and team • Support with a personalized development plan aligned to your goals • Darwin – global program to develop young talent, building soft and hard skills • Grounding – a global onboarding program for newly hired professionals starting their consulting careers • Induction – international onboarding led by HR and business leaders to introduce BIP's culture, values, purpose, and global programs • Spinnaker – training focused on enhancing strategic skills for Managers and Senior Managers, supporting business development within a complex ecosystem