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Matrix Global
Matrix Global
51 – 200 Employees
ConsultingFood & BeverageLogistics
Matrix Global develops digital marketplaces for transactions in the oil and gas midstream sector. Its proprietary MAP platform supports auctions for storage and pipeline capacity, helping energy companies and storage providers compare opportunities, improve market transparency, and manage exposure through short- and long-term contracts. The company works with industry participants to make storage transactions more competitive and operationally informed.
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Data Scientist - Europe Remote

Join Matrix Global as a Data Scientist developing scalable machine learning and analytics solutions. This customer-facing role covers data modeling, deployment, and collaboration with technical and business stakeholders.

EUEuropean UnionRemoteFull-timeJuniorMiddleEnglish RequiredData Scientist
AirflowCloudPySparkPython

Description

  • Deliver data science solutions across the full project lifecycle
  • Examine complex, high-volume datasets to uncover trends, anomalies, and actionable findings
  • Create and refine machine learning models and advanced analytics workflows
  • Prepare data and engineer features for predictive modeling projects
  • Work with Product, Engineering, and Customer Success to convert business needs into technical solutions
  • Own data science activities for customer implementations, pilots, and production releases
  • Develop trusted technical partnerships with customers and external collaborators
  • Recommend improvements to products, algorithms, and analytical capabilities
  • Provide training and transfer knowledge to users and stakeholders
  • Investigate and help resolve data and analytics issues

Requirements

  • Bachelor's degree in data science, computer science, mathematics, statistics, economics, or a related quantitative discipline
  • At least two years of experience in data science, data engineering, machine learning, or big data development
  • Advanced Python programming ability
  • Professional experience with PySpark
  • Practical knowledge of large-scale data processing frameworks and machine learning pipelines
  • Experience managing machine learning lifecycles with MLflow, Airflow, or comparable workflow tools
  • Strong analytical, statistical modeling, and problem-solving capabilities
  • Ability to explain complex technical ideas to both technical and non-technical audiences
  • Customer-facing or external stakeholder experience is advantageous
  • Background in financial services, fraud detection, risk analytics, compliance, or transaction monitoring is preferred
  • Familiarity with cloud-based data and machine learning environments is preferred
  • Experience identifying anomalies and deriving insights from high-volume data is preferred
  • Knowledge of best practices for deploying and monitoring machine learning models is preferred

Benefits

  • Competitive compensation and benefits package
  • Opportunities for meaningful career progression
  • Diverse and inclusive workplace culture
  • A collaborative environment focused on continuous learning and growth
  • Work alongside a skilled global team
  • Contribute to technically meaningful initiatives
  • Opportunities to provide and receive training and knowledge transfer

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