Principal Data Scientist (for Greece) (Town of Greece)

About the client

Our client is a global technology company with a strong focus on AI innovation, large‑scale data applications, and modern product delivery. Operating in multiple international markets, the company encourages autonomy, experimentation, and engineering leadership in all areas of data science and machine learning. Teams are cross‑functional, highly collaborative, and empowered to bring real business impact through AI‑driven solutions.

Role Highlights:

• Position: Principal Data Scientist
• Type of work: Hybrid from Athens.
• Work from office requirements: 2 days per week from the office, 3 days per week from the office. 100% remote option is NOT possible.
• Type of contract: Full‑time employment contract.
• Contract location: Greece
• Type of company: International growing tech company with operations in 15+ markets with around 2,500 employees across several continents.
• Years of experience required: 9+ years of experience.
• Must‑have tech skills: experience leveraging large‑scale data to build ML/DL models with Python, MLOps, experience in GenAI application development (nice to have: big data technologies).
• Industry: Information technology, entertainment
• Relocation support: Relocation support for Greek expats.
• Bonuses, perks, benefits: competitive pay and bonus scheme, career development, monthly meal allowance, private health insurance for the employee and their family members, continuous training and unlimited access to Udemy.
• Reasons why it is a great place to work? International company, growing team, exciting project, the company is among the Best Workplaces in Europe and certified Great Place to Work across their offices.
• Work permit requirements: Only candidates with valid work permit for European Union (EU) will be evaluated for this role.

About the role

As a Principal Data Scientist, you will be responsible for leading the design, development, and deployment of advanced machine learning and deep learning systems. You’ll guide the technical roadmap for AI initiatives, mentor other scientists, and drive innovation with scalable, production‑ready solutions. This role is ideal for a senior AI professional with both strategic vision and deep technical expertise across multiple ML disciplines.

Tech stack

Projects are implemented using Python and its broader ML ecosystem, with production‑level MLOps practices. The infrastructure may include big data tools such as Apache Spark, Delta Lake, Kafka, and Flink. Experience with foundational models, prompt engineering, or GenAI platforms is also a plus.

What will you do

• Design scalable architectures and cutting‑edge algorithms for AI‑powered systems.
• Lead the technical direction of the AI team, aligning with product and business objectives.
• Own the entire lifecycle of AI projects, from ideation and experimentation to production and monitoring.
• Deliver high‑impact proofs of concept that demonstrate measurable business value.
• Mentor senior and junior data scientists across technical and professional development areas.
• Guide strategic prioritization of AI initiatives, balancing innovation with value delivery.
• Explore and apply the latest advancements in AI research to stay at the forefront of the field.
• Communicate technical strategies effectively across both technical and non‑technical stakeholders.

Ideally you bring

• 8+ years of experience designing, implementing, and deploying ML/DL models in production environments using Python.
• PhD‑level expertise (or equivalent experience) in one or more of the following: recommender systems, NLP, computer vision, speech/audio processing, time‑series modeling, reinforcement learning, graph‑based learning.
• Strong understanding of the ML lifecycle, including data pipelines, training, evaluation, deployment, and monitoring.
• Solid experience with MLOps tools and practices for maintaining robust AI systems at scale.
• Proven ability to drive architecture decisions, model optimization, and scalability improvements.
• Strong communication and stakeholder management skills across technical and business teams.
• (Nice to have) Practical experience with GenAI systems or agent‑based AI workflows, including prompt engineering and model evaluation techniques.
• (Nice to have) Familiarity with distributed data technologies such as Spark, Delta Lake, Kafka, or NoSQL systems.

Compensation & Benefits

Attractive salary plus performance‑based incentives, opportunities for professional growth, monthly meal package, private health coverage, and continuous education and skill‑building resources.

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