Data Scientist Job at DRAXIS ENVIRONMENTAL S.A., Hellenic Republic

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  • DRAXIS ENVIRONMENTAL S.A.
  • Hellenic Republic

Job Description

DRAXIS is an SME that focuses on developing real life environmental scientific solutions. Looking always ahead, we keep up with and interpret what is happening in day-to-day business, so as to offer custom-made tools, reflecting our commitment to be of service to the environment we live in. 

We are currently seeking a highly motivated and experienced Data Scientist to join our team. As a Data Scientist at DRAXIS, you will contribute to cutting-edge AI research and drive the design and implementation of machine learning solutions in the context of R&D projects and product development. You will collaborate with multidisciplinary teams to translate domain-specific challenges into deployable and scalable ML solutions. 

Responsibilities

  • Collaborate with domain experts and developers to design and deploy scalable machine learning models.

  • Work on cutting-edge AI/ML applications in agriculture, remote sensing and environmental domains, as part of both product development and European R&D projects.

  • Develop end-to-end ML pipelines: from designing data collection strategies and preprocessing workflows to model training and deployment.

  • Apply techniques such as time series forecasting , deterministic methods (e.g. neural networks), and generative AI (GenAI) to solve real-world challenges.

  • Translate functional and business requirements into technical solutions, aligning with be practices in ML.

  • Contribute to technical documentation, testing, and dissemination of project outcomes (including possible scientific publications or open-source contributions)

Requirements

  • Bachelor’s/Master’s degree in the field of Computer Science and/or Data Science, Machine Learning, or a related field.
  • Strong understanding of machine learning algorithms, neural networks, and statistical methods.
  • Proficiency in Python , including experience with libraries like Pandas, NumPy, Scikit-learn, etc.
  • Hands-on experience with ML/DL frameworks such as TensorFlow , PyTorch , and Keras .
  • At least 2 years of proven professional experience in applying machine learning technologies in one or more of the following areas: Time series analytics, deterministic mathematical functions and stochastic methods.
  • Proficiency in Linux environments and cloud-based ML tools/workflows.
  • Excellent knowledge of English (both written & spoken).
  • Solid grounding in machine learning fundamentals: supervised and unsupervised learning, model evaluation, and statistical methods.

Preferred qualifications

  • PhD Degree in a related field (e.g., AI/ML, Applied Mathematics, Data Science).

  • Experience in leading or contributing to EU-funded R&D projects (e.g., Horizon Europe, Digital Europe).

  • Open-source contributions or published research in top-tier ML conferences (NeurIPS, ICML, ACL, etc.).

  • Experience working with agronomic, geospatial, or environmental data (or strong interest in applying ML to these domains).

  • Familiarity with distributed systems and data streaming tools such as Apache Spark and Kafka .

Benefits

By joining DRAXIS , you will be able to engage with fellow professionals in your field across diverse markets, fostering valuable connections. This network will provide opportunities to exchange best practices, collaborate on overcoming challenges, and gain invaluable experience and mentoring to propel your career forward. At DRAXIS , we are committed to helping you shape the career you desire, empowering you to chart your own path towards success.

At DRAXIS , we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health benefits, as well as professional development and tuition assistance. At the core of our culture is a strong emphasis on prioritizing people. We value the advantages of both flexibility and collaboration, whether they occur in a physical workplace or in a remote setting.

Job Tags

Remote job,

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