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18 May 
18 May
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At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.
Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 700 experts from 35+ countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.
We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination. Are you ready to embark on this exciting journey with us?
We make things happen
We act decisively and with purpose, going the extra mile.
We build
together
We foster relationships and develop creative solutions to address market challenges.
We are here to help
We are accessible and supportive to colleagues and clients with a friendly approach.
Our People Pledge
Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.
Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.
By applying, I confirm that I have read and accept the Staff Privacy Notice
Responsibilities
- Develop and maintain production-grade machine learning and image analysis pipelines.
- Apply statistical, machine learning, computer vision, or signal-processing techniques to satellite and drone imagery datasets.
- Analyse and process satellite imagery (SAR, optical, and others) or geospatial time series to detect, classify, and monitor physical activity and assets over time.
- Contribute to the integration of multiple satellite or drone data providers and heterogeneous image sources.
- Collaborate with data engineers and software engineers to integrate model outputs into APIs and customer-facing products.
- Improve model robustness, performance, and interpretability over time.
- Translate research or experimental code into reliable, production-ready workflows.
- Document methodologies and share knowledge to support team-wide best practices.
Skills and Experience
- 3–6 years of experience in data science, applied machine learning, computer vision, or remote sensing / geospatial engineering.
- Strong proficiency in Python for data processing, modelling, and pipeline development (numpy, pandas, scikit-learn, etc.).
- Solid experience with data manipulation, cleaning, and feature engineering on real-world, noisy datasets.
- Experience working with satellite imagery, geospatial data, and time-series datasets.
- Proven track record of turning experimental or research code into production-ready workflows.
- Solid understanding of software engineering best practices (version control, testing, code review).
Nice to have
- Significant experience in general Computer Vision, including object detection, semantic segmentation, change detection, or anomaly detection.
- Proficiency with CV/ML frameworks such as PyTorch, TensorFlow, or OpenCV.
- Experience working with multiple commercial or open-source satellite data providers.
- Experience with drone (UAV) imagery processing and advanced geometry computation (e.g., photogrammetry, coordinate transformations, or 3D reconstruction).
- Knowledge of Radiometry and Radiometric Calibration.
- Familiarity with data orchestration tools like Airflow.
- Cloud infrastructure experience (AWS/GCP) and database knowledge (SQL/Postgres/PostGIS).
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