Job Description

Accelerate your development and exposure to high‑performance data platforms and cloud infrastructure. Join Sedona Digital, a fast‑growing scale‑up with the ambition to be recognised as one of the leading technology companies in Romania.

Our global client base needs builders, engineers who enjoy designing and implementing scalable data platforms, have deep expertise in cloud data technologies, and take pride in delivering reliable, well‑governed solutions.

At Sedona, we:

• Obsess about our customers
• Build robust, scalable technical solutions
• Create an open, collaborative culture
• Invest in learning and long‑term careers

We are looking for a Senior Data Scientist with strong expertise in machine learning, advanced analytics, and statistical modeling to design and deliver data-driven solutions that generate measurable business impact.

The role focuses on translating complex business problems into analytical models, developing robust machine learning solutions, and communicating insights effectively to stakeholders, while leveraging Azure data and AI services as an enabling platform.

Responsibilities

• Translate business problems into analytical solutions, identifying opportunities for predictive modeling, optimization, and data-driven decision-making
• Design, develop, and deploy machine learning models using techniques such as classification, regression, clustering, and forecasting
• Apply statistical methods and experimentation techniques (hypothesis testing, A/B testing) to validate models and insights
• Conduct exploratory data analysis (EDA) to identify patterns, trends, and key drivers within large datasets
• Engineer features and prepare datasets to improve model performance and robustness
• Evaluate and optimize models using appropriate metrics, cross-validation, and tuning strategies
• Ensure model explainability and interpretability, communicating results clearly to both technical and non-technical stakeholders
• Design and implement MLOps practices including model versioning, monitoring, and retraining strategies

• Collaborate with data engineers to access, prepare, and scale datasets from Azure-based platforms (Synapse, ADLS, SQL)
• Present insights and recommendations through compelling storytelling and data visualization (Power BI or similar tools)
• Contribute to the design of analytics and AI solutions, focusing on delivering business value rather than infrastructure
• Engage with stakeholders and clients during discovery, experimentation, and solution design phases

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field
• 5+ years of experience in Data Science, Machine Learning, or Advanced Analytics roles
• Strong hands-on experience with:

• Machine Learning techniques (regression, classification, clustering, time series, etc.)
• Statistical analysis and modeling
• Python ecosystem (pandas, scikit-learn, NumPy, PySpark)
• Experience with:
• End-to-end ML lifecycle (data preparation, modeling, evaluation, deployment, monitoring)
• Model performance tuning and validation techniques
• Strong SQL skills and experience working with large datasets
• Experience deploying models into production environments
• Ability to communicate complex analytical concepts clearly to business stakeholders
• Strong problem-solving mindset with the ability to work independently and make pragmatic decisions

Preferred Skills (Nice to Have)

• Experience with Azure Machine Learning (Azure ML) or similar ML platforms
• Familiarity with MLOps frameworks and model lifecycle management
• Experience with experiment tracking and model monitoring tools
• Knowledge of CI/CD practices for ML pipelines
• Experience working in regulated or data-sensitive environments
• Previous involvement in client-facing data science engagements

Key Tools & Technologies

• Azure ML, Azure Synapse, Azure Blob Storage / ADLS
• Azure DevOps, GitHub
• Python, SQL
• Miro, Figma

Benefits

• Remote Work Flexibility
• Opportunity to work in a rapidly growing scale-up organisation
• Exposure to complex, global client engagements
• Training on market trends and client needs
• Ongoing learning and development opportunities
• Competitive compensation package
• Fun budget for team events