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Senior Data Scientist

3 months ago
Serbia, Romania
Contract
Senior
Data Scientist
Data Science and Analytics
Apache Spark Azure CI/CD Feature Engineering Figma GitHub Machine Learning MLOps NumPy Pandas Power BI Python Scikit-learn SQL
Apply Now

Sedona Digital

Sedona Digital describes itself as an award-winning transformation partner specializing in Software/AI, Data/AI, Cloud Security, and Business Change. Its site also describes it as a process-led, AI, data, security and software business.

IT Services and IT Consulting
Founded 2008
View All Jobs 8

Description

  • Translate business problems into analytical solutions for predictive modeling, optimization, and data-driven decision-making.
  • Design, develop, and deploy machine learning models for classification, regression, clustering, forecasting, and other predictive tasks.
  • Apply statistical methods and experimentation techniques, including hypothesis testing and A/B testing, to validate models and insights.
  • Conduct exploratory data analysis to identify patterns, trends, and key drivers in 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, and communicate results to 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 such as Synapse, ADLS, and SQL.
  • Present insights and recommendations through storytelling and data visualization tools such as Power BI.
  • 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 such as regression, classification, clustering, and time series.
  • Strong hands-on experience with statistical analysis and modeling.
  • Strong hands-on experience with the Python ecosystem, including pandas, scikit-learn, NumPy, and PySpark.
  • Experience across the end-to-end machine learning lifecycle, including data preparation, modeling, evaluation, deployment, and monitoring.
  • Experience with 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.
  • Experience with Azure Machine Learning or similar ML platforms, preferred.
  • Familiarity with MLOps frameworks and model lifecycle management, preferred.
  • Experience with experiment tracking and model monitoring tools, preferred.
  • Knowledge of CI/CD practices for machine learning pipelines, preferred.
  • Experience working in regulated or data-sensitive environments, preferred.
  • Previous involvement in client-facing data science engagements, preferred.

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.

Interested in this position?

Apply directly on the company website

Apply Now

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