Data Scientist

We are looking for a Forward Deployed Data Scientist to join our team. This is a hands-on, client-facing role that sits at the intersection of data science and engineering. You'll work directly with clients to deploy, adapt, and integrate JTA's data science and machine learning solutions into their real-world environments, bridging the gap between the models and systems we build and the operational needs on the ground. You'll combine strong data science know-how with solid software engineering skills to make sure our solutions deliver tangible, measurable value in production.

What you will be doing:

• Work closely with clients to understand their data landscape, technical environment, and business objectives, translating these into effective data science deployment strategies.
• Deploy, configure, and integrate JTA's data science and ML solutions into client systems, ensuring models run reliably and deliver value in production.
• Adapt and extend existing models and data pipelines to fit client-specific data, constraints, and requirements, writing robust, maintainable code across the stack.
• Act as a technical bridge between clients and JTA's internal data science and engineering teams, relaying feedback and shaping solutions accordingly.
• Troubleshoot issues across data pipelines and production models, monitoring performance and providing hands-on support to ensure solutions perform as intended.
• Collaborate with business stakeholders and the sales team to translate data science outcomes into clear business value.

Requirements:

• Bachelor's or Master's in Data Science, Computer Science, Software Engineering, or a related field.
• 3+ years of experience in data science, machine learning deployment, or a similar hands-on technical role.
• Solid understanding of data science and machine learning concepts, with practical experience adapting models to real-world data and constraints.
• Strong programming skills in Python, including the data science ecosystem (e.g. pandas, scikit-learn), with solid software engineering fundamentals (version control, testing, CI/CD).
• Experience with PySpark for large-scale data processing and feature engineering.
• Experience deploying and integrating data science solutions in client or production environments, including working with APIs, cloud platforms, and containerization (e.g., Docker).
• Familiarity with distributed systems and the challenges of building and operating data-intensive solutions at scale.
• Excellent communication skills and a client-focused mindset, with the ability to explain models and technical concepts to non-technical stakeholders.
• Strong problem-solving skills and the ability to work independently in ambiguous, fast-moving situations.
• Willingness to travel to client sites when needed.

Perks:

• Annual gross salary between €30,000 and €40,000, depending on experience and qualifications, with room for flexibility;
• Flexible Hybrid Work System;
• 15th Month Bonus Salary Policy;
• 4 extra vacation days;
• Participation in International Projects;
• Company-Paid Certifications;
• Training, career progression and support;
• Team Building Activities;
• Innovative & Young Culture.