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Senior Data Scientist
Résumé du poste par JobGrid
Senior Data Scientist at Sedona Digital: Remote, Roumanie; Contrat; Senior; IT; Data Science et ML. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Remote, Roumanie
- Role classification: IT, Data Science et ML, Contrat, Senior
- Source freshness: checked by JobGrid on 2026-05-29.
- Application path: candidates continue to the employer application page with non-personal referral tags.
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