Sedona Digital
Information Technology and Services
SeniorDataScientist
“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
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