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Mid-level, metro Data Scientist role with generalist ML requirements increases applicant competition.
Core ML and model-deployment skills are transferable, but Salesforce integration/context raises domain specificity.
Explicit 4+ years, required ML stack and production deployment make screening stringent.
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Own end-to-end data science projects including predictive modeling and production deployment.
Develop and deploy ML models using Python, SQL, and associated libraries like Pandas, Scikit-learn, and NumPy.
Manage data integration and feature engineering for both structured and unstructured data, including model documentation and experiment tracking.
4+ years of hands-on experience in Data Science and Predictive Modeling in production environments.
Proficiency in Python and SQL with libraries Pandas, Scikit-learn, NumPy.
3+ years experience with Statistical Analysis, ML algorithms, and production model deployment.
Location requirement: Hybrid work mode based in Hyderabad.
Experienced in managing end-to-end data science projects with measurable business impact.
Skilled in experiment tracking tools like MLflow, DVC, or Jupyter notebooks for model documentation.
Comfortable working independently with strong analytical, mathematical, and communication skills to translate data findings into business insights.