Kpler

About Kpler

Transforming trade with data-driven insights

🏢 Tech, Corporate👥 201-500 employees📅 Founded 2014📍 Etterbeek, Brussels💰 $220m3.1
B2BArtificial IntelligenceEnergyBig dataDeep TechMachine LearningSaaSMobile

Key Highlights

  • Raised $220 million in funding for expansion
  • Acquired five companies between 2022 and 2023
  • Leader in commodity market data with ten times the revenue of competitors
  • Headquartered in Etterbeek, Brussels with 201-500 employees

Kpler, headquartered in Etterbeek, Brussels, is a leader in providing data and analytics for the commodity trading industry. Founded in 2014, Kpler has raised $220 million in funding and has acquired five companies between 2022 and 2023 to enhance its offerings. The company serves a diverse range of...

🎁 Benefits

Kpler offers a flexible office policy allowing employees to choose between co-working spaces, office locations, or full remote work. Employees receive...

🌟 Culture

Kpler fosters a culture of innovation by leveraging advanced data technology to transform the traditionally archaic commodity trading industry. The co...

Overview

Kpler is hiring a Data Scientist specializing in Remote Sensing to work with complex geospatial data and satellite imagery. You'll leverage your skills in Python and machine learning to transform data into actionable insights. This position is designed for mid-level professionals with a passion for applied remote sensing.

Job Description

Who you are

You are a mid-level Data Scientist or Remote Sensing Engineer with a strong background in applied remote sensing and experience working with complex geospatial data. You have a solid understanding of satellite imagery, particularly SAR imagery, and are comfortable transforming intricate data into actionable insights. Your expertise in Python and machine learning allows you to develop algorithms that evolve from research into production systems. You enjoy collaborating with a diverse team and are eager to contribute to innovative data products that impact global trade information.

You have experience with remote sensing technologies and are familiar with platforms that integrate multiple satellite providers and sensing modalities. Your analytical skills enable you to navigate complex datasets and derive meaningful conclusions that support decision-making in commodities, energy, and maritime sectors. You are detail-oriented and possess strong problem-solving abilities, which help you tackle challenges in data processing and analysis.

What you'll do

In this role, you will work closely with the remote sensing team to develop and enhance data products that utilize satellite imagery. You will be responsible for analyzing SAR and optical imagery, ensuring that the data is transformed into reliable operational insights. Your work will involve designing and implementing algorithms that improve the accuracy and efficiency of data processing workflows. You will collaborate with other data scientists and engineers to integrate new satellite data sources into existing platforms, enhancing the overall functionality and user experience.

You will also engage in research activities to explore new methodologies in remote sensing and data analysis, contributing to the continuous improvement of Kpler's offerings. Your role will require you to communicate findings effectively to stakeholders, translating complex technical concepts into understandable insights that drive business decisions. You will have the opportunity to mentor junior team members, sharing your knowledge and expertise in remote sensing and data science.

What we offer

Kpler provides a dynamic work environment where innovation and collaboration are at the forefront. You will be part of a team of over 700 experts from diverse backgrounds, all dedicated to transforming global trade information. We offer competitive compensation and benefits, along with opportunities for professional growth and development. Join us to leverage cutting-edge technology and make a significant impact in the commodities, energy, and maritime sectors.

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