Senior Data Scientist

Key Qualifications Experience: 1–2 years of software development experience (preferred) 1–2 years of experience as a Data Scientist, with a focus on Time Series forecasting 4+ years working with Azure Cloud platforms , including: Azure Databricks Azure ML Studio Azure Data Factory (ADF) Pipelines Technical Skills: ML Ops / DevOps practices and tooling CI/CD pipeline configuration and deployment MLFlow for experiment tracking and model management Strong programming skills in Python Experience with machine learning models such as: Random Forest XGBoost LightGBM Other ensemble modeling algorithms Education: Bachelor's or Master's degree in Software Engineering, Computer Science, Statistics, or a related field PhD not required Soft Skills: Fast learner with the ability to adapt to changing priorities Strong problem-solving and collaboration skills Role Responsibilities Function as a developer with a strong focus on: ML model implementation , experimentation , and deployment Applying software engineering best practices in machine learning projects Conduct data analysis and work with forecasting algorithms , especially for time series data Collaborate with cross-functional teams to deliver production-level ML solutions Tools & Technologies Azure Databricks Azure ML Studio Azure Data Factory (ADF) MLFlow CI/CD tools (e.g., GitHub Actions, Azure DevOps, Jenkins) Python and relevant ML libraries (e.g., scikit-learn, pandas, numpy, etc.) What We Offer Opportunity to work on cutting-edge ML projects A highly motivated and collaborative team Competitive salary Flexible schedule Benefits package including: Medical insurance Sports membership or wellness stipend Corporate social events Professional development opportunities Modern, well-equipped office environment