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Mid-level data science role in Bangalore with common skillset and broad requirements, so highly competitive.
Core data science skills are transferable, though automotive risk specialization increases domain specificity.
Explicit 3–6 years requirement plus mandatory Python and SQL makes screening moderately strict.
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Develop, validate, and document machine learning predictive models focused on automotive risk and finance use cases.
Extract and analyze large-scale datasets using SQL, delivering actionable insights and clear documentation to clients.
Own end-to-end deliverables in a client-facing capacity as an individual contributor, enhancing traditional finance models with statistical methodologies.
3 to 6 years of experience in Data Science or Predictive Analytics.
Proficiency in Python and SQL with hands-on expertise.
Experience in statistical modeling, regression analysis, machine learning algorithms, model validation, and documentation.
Location requirement: Bengaluru, Karnataka, India.
Experience working with automotive industry clients, especially OEMs and Tier-1 suppliers, focusing on risk and finance modeling.
Ability to independently manage deliverables and communicate technical insights effectively in client-facing roles.
Exposure to Google Cloud Platform (GCP) is a strong advantage.