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This role involves building and delivering advanced data science and AI/ML solutions in an agile environment, with a focus on rapid iteration and business impact. The Data Science Lead will drive end-to-end model development, including propensity modeling and integration with data engineering pipelines, while leveraging GenAI to accelerate outcomes. Supporting roles include Data Scientists and Data Engineers who will collaborate to build models, manage data pipelines, and ensure scalable data infrastructure. Experience in the HR domain is a plus.

Requirements:
​Data Science Lead (SC or M level) – should have experience leading data science project with rapid iterations in an agile manner.

Should have experience developing AI/ML propensity modeling experience and in driving data engineering to support the model development and refinement.

Driving the use of Data Assist or GenAI to accelerate the project would be great. Experience in HR domain would be ideal!
Data Science Support (SC or C level) – Should have AI/ML experience and be able to take direction and develop model as part of a team
Data engineer (C level) – should have experience building pipelines in AWS and cloud databases. Structured and unstructured data sets. Loading of data into S3 as well as tabular schemas. Databricks experience preferred.​

Responsibilities:
Lead end-to-end data science projects using agile and iterative approaches.
Develop and deploy AI/ML models, including propensity modeling.
Drive data engineering requirements to support model development and optimization.
Leverage GenAI/Data Assist tools to accelerate data science workflows.
Collaborate with stakeholders to align models with business outcomes.
Build and refine machine learning models under guidance.
Perform data analysis, feature engineering, and model validation.
Support deployment and testing of AI/ML solutions.
Reference : Data Scientist jobs

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Published at 19-04-2026
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