Senior Data Scientist

This is a fully remote position, open to applicants in Macedonia.

📋 Description

• Lead the implementation of advanced analytics, causal reasoning, and AI-driven decision intelligence across various applications within our AI portfolio.

• Operate at the crossroads of data science, machine learning, and Generative AI, transforming intricate data into actionable insights, automated decisions, and intelligent workflows.

• Create and implement systems that combine experimentation, observational data, machine learning, and generative AI for real-time or near-real-time decision-making pipelines.

• Work collaboratively with data engineers, machine learning engineers, analysts, and platform teams, contributing to shared modeling standards and a cross-functional AI architecture.

• Develop and implement machine learning models for diverse use cases, including forecasting, optimization, and recommendation systems.

• Utilize statistical, predictive, and prescriptive modeling techniques to address business challenges.

• Construct reusable modeling frameworks that can be scaled across various domains.

• Design and execute causal inference methods such as uplift modeling, experiments, and quasi-experimental techniques.

• Convert observational and experimental data into actionable insights for the business.

• Incorporate causal reasoning into decision systems that inform actions such as optimization, prioritization, and trade-offs.

• Integrate generative AI capabilities, including large language models, retrieval-augmented generation pipelines, and agent-based systems into data science workflows.

• Contribute to the creation of intelligent agents and AI-supported decision-making systems.

• Merge structured data models with unstructured data and outputs from generative AI.

⛳️ Requirements

• Extensive experience in machine learning, statistics, and applied data science.

• Familiarity with causal inference, experimentation, or decision science methodologies.

• Strong understanding of forecasting, optimization, or analytical modeling techniques.

• Proficient programming skills in Python and SQL.

• Experience in building and deploying production-ready data science or machine learning systems.

• Knowledge of model lifecycle management, encompassing training, deployment, and monitoring.

• Practical experience with at least one major cloud platform: Azure (preferred), AWS, or GCP.

• Experience handling complex, multi-source datasets, including transactional, behavioral, and operational data.

• Capability to translate business issues into analytical frameworks.

• Strong problem-solving skills with an emphasis on business impact.

• Ability to convert complex models into actionable decisions.

• Excellent collaboration and communication skills across both technical and business teams.

🏝️ Benefits

• Private health insurance

• Education program

• Wellbeing program

• Free beverages

• Events

• Competitive conditions

• Challenging projects

• Cool colleagues

• Honest feedback