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Popular Data Scientist title, metro locations, mid-level range, and broad ML skillset increase applicant density.
Technical ML skills are transferable, but client-facing analytics and domain knowledge raise fit specificity.
Explicit 5.6–11 years requirement plus mandatory R/Python and end-to-end ML experience raises filter strictness.
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Lead and manage a team of Data Scientists working on AI/ML solutions across various business domains.
Independently design, develop, and implement advanced statistical and machine learning algorithms to solve business problems like Customer Segmentation, Churn Modelling, Forecasting, and Pricing Optimization.
Collaborate with stakeholders and cross-functional teams to identify opportunities, deliver end-to-end data science solutions, and monitor model outcomes.
5.6-11 years of work experience in core Data Science and Machine Learning projects.
Expert proficiency in at least one programming language: R or Python.
Strong skills in data structures, machine learning algorithms, and full data science pipeline experience (problem scoping, data gathering, EDA, modeling, insights, visualization, monitoring, maintenance).
Work Experience Required: 5.6-11 years.
Experienced leader capable of managing and mentoring a span of Data Scientists and strong stakeholder relationships.
Able to work independently on complex AI/ML research and projects with leadership and ownership mindset.
Comfortable working in fast-paced environments delivering solutions across multiple domains with end-to-end delivery responsibility.