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You will lead end-to-end data science workstreams, serving as a technical authority for AI solution design and feasibility assessments. You will collaborate directly with stakeholders to translate business needs into reliable, high-impact AI and machine learning applications.
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.
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.
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.
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.
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
100% paid sick leave
Private health insurance
MultiSport / PassSport card subsidy
Meal allowance
Transportation/WFH allowance
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.
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