Sedona Digital
Information Technology and Services
SeniorDataScientist
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“Senior Data Scientist at Sedona Digital. Skills: Machine Learning, Statistical Modeling, Python, Azure. Translate business problems into analytical solutions. Design, develop, and deploy machine learning models”
What You'll Achieve.
deliver reliable, well-governed solutions; generate measurable business impact; delivering business value rather than infrastructure
Industry & Context.
problem-solving mindset; ability to work independently and make pragmatic decisions
What They're Looking For.
Must Have
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, hands-on experience with Machine Learning techniques (regression, classification, clustering, time series, etc.), hands-on experience with Statistical analysis and modeling, hands-on experience with Python ecosystem (pandas, scikit-learn, NumPy, PySpark), Experience with end-to-end ML lifecycle (data preparation, modeling, evaluation, deployment, monitoring), Experience with Model performance tuning and validation techniques, SQL skills and experience working with large datasets, Experience deploying models into production environments, Ability to communicate complex analytical concepts clearly to business stakeholders, problem-solving mindset
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
What You'll Do.
Translate business problems into analytical solutions
and deploy machine learning models
Apply statistical methods and experimentation techniques
Conduct exploratory data analysis
Engineer features and prepare datasets
Evaluate and optimize models
Ensure model explainability and interpretability
Design and implement MLOps practices
Collaborate with data engineers
Present insights and recommendations
Contribute to the design of analytics and AI solutions
Engage with stakeholders and clients
How You'll Work.
Team & Collaboration
Collaborate with data engineers to access, prepare, and scale datasets; Engage with stakeholders and clients during discovery, experimentation, and solution design phases
Communication Scope
communicating insights effectively to stakeholders; communicating results clearly to both technical and non-technical stakeholders; Ability to communicate complex analytical concepts clearly to business stakeholders; compelling storytelling
Full 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
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