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Mid-level ML role at a known brand in Mumbai with broad skillset increases competition.
ML and CV skills are transferable but geospatial/point-cloud specificity raises domain sensitivity.
Explicit 3–8 years plus mandatory ML, CV, deep-learning and big-data skills implies high strictness.
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Design and build scalable Big Data and machine learning-based automation for global-scale digital map-making processes.
Develop, deploy, and maintain analytic and predictive models to improve internal data-driven map-making decisions and system controls.
Lead predictive modeling or application teams on Core Map projects and serve as an expert in data mining, machine learning, and predictive analysis.
Bachelor's, MS, or PhD in Statistics, Applied Mathematics, Computer Science, Econometrics, or related field with emphasis on computational stats, data mining, machine learning.
3-8 years of related work experience depending on educational qualification.
Proficiency in statistical analysis tools (e.g., Python, R, Matlab, SAS) and programming languages (SQL, shell script, Python).
Experience with Big Data tools such as Pig, Hive, Hadoop, Spark, and NoSQL databases (e.g., DynamoDB).
Experienced in advanced data mining methods including regression, classifiers, clustering, Bayesian networks, and decision trees with expert-level knowledge in one or more areas.
Proven ability to lead teams of data scientists and engineers delivering predictive modeling solutions.
Capacity to effectively communicate and collaborate with both technical and non-technical stakeholders, including executives.