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Are you a Data Scientist with a strong quantitative foundation and hands-on experience in applied AI and LLM architecture? Do you enjoy bridging the gap between complex data solutions and business strategy by engaging directly with stakeholders?
We are looking for a Senior Data Scientist (Applied AI) to join our team. In this role, you will lead end-to-end data science workstreams, perform feasibility assessments, and design modern AI-driven solutions—from core statistical modelling to production-grade LLM applications and agents.
Your Role
You will own data science workstreams end-to-end, serving as both a technical authority and a key driver for AI solution design. You will work directly with stakeholders to validate feasibility, design architectures, and deliver reliable, high-impact data and AI applications.
What is it all about?
Core Machine Learning & Time Series:Develop predictive models and feature engineering solutions, with a strong focus on time series, predictive analytics, and classical statistical inference.
Applied AI & LLM Workflows:Build, evaluate, and deploy working LLM applications, including custom agents, retrieval-augmented generation (RAG) over text and document data, API integration, and structured workflows.
Prompt Engineering & Evaluation:Design robust prompts and establish structured testing methodologies to ensure LLM outputs are accurate, consistent, and reliable.
Cloud & Tech Ecosystem:Build primarily in Python, leveraging Azure AI Foundry for AI/ML development and Microsoft Copilot Studio for lighter agent workflows. Extract and query data across AWS (S3, Redshift) and Azure environments.
Feasibility & Solution Design:Conduct early-stage feasibility assessments, shape technical approaches before development, and design viable, end-to-end data/AI architectures.
Stakeholder Engagement:Work directly with technical and non-technical stakeholders to present findings clearly, translate business needs into technical solutions, and inform decisions through solid statistical reasoning.
What do we expect from you?
Education:MSs in a quantitative field (Mathematics, Statistics, Computer Science, Physics, Data Science, etc.). PhD is a big plus.
Experience:At least 5+ years of hands-on experience successfully delivering data science and machine learning projects end-to-end.
Data Science & ML Core:Strong quantitative background with proficiency in statistical analysis (descriptive & inferential), time series, predictive modelling, feature engineering, and model validation.
Applied AI Skills:Hands-on experience building LLM applications via APIs/connectors, implementing RAG architectures, prompt engineering, and building data-driven AI agents.
Tech Stack & Cloud:High proficiency in Python. Experience with Azure (Azure AI Foundry, data stores), AWS (S3, Redshift for data retrieval), and familiarity with Microsoft Copilot Studio.
Functional Capabilities:Strong critical thinking (validating both human and AI outputs), high autonomy, adaptability, and excellent stakeholder management skills.
What Q offers you
Flexible working hours & remote work, but restricted exclusively to working from Croatia, Serbia, or BiH (we do not offer a relocation option)
Diverse international clients and high-impact projects
Internal workshops and continuous professional development
Salary Range
Our compensation model is based on your overall experience, depth of knowledge, and performance during the interview process.
Up to €5,000.00 Gross 1 for the full-time engagement.
Sounds like your next challenge? Click the button below and apply now!
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