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Popular ML role, metro Mumbai location, and mid-level (5-7 years) experience increase competition.
Core ML modelling skills transfer across industries, but sports analytics and published rating experience increase domain specificity.
Explicit 5+ years, mandatory production ML experience, modelling ownership, and required statistics skills make screening strict.
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Design, build, validate, and productionize predictive and descriptive machine learning models using live and historical sports data.
Own end-to-end modelling decisions including problem definition, feature engineering, validation, production integration, and continuous improvement of model accuracy and robustness.
Collaborate with Product, Data, Backend teams and non-technical stakeholders to translate business questions into modelling solutions and ensure meaningful product outcomes.
5+ years of experience building and deploying statistical or machine learning models in production.
Strong proficiency in Python and SQL with experience working on large, complex, messy event-level sports or transactional data.
Strong foundation in applied statistics including probabilistic modelling, regression, time-series, and model validation.
Work Experience Required: Minimum 5 years relevant ML/statistics experience; Location: Goregaon, Mumbai, Maharashtra, India.
Experience owning modelling decisions end-to-end, beyond just implementation, with strong analytical judgment on model complexity and robustness.
Ability to communicate modelling methodologies, assumptions, and trade-offs clearly to non-technical stakeholders including product and sports domain experts.
Domain familiarity or interest in sports analytics, preferably cricket, valuing delivery of reliable intelligence models that impact real-world sports analysis and prediction.