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Tier-1 brand, popular data scientist title, and mid-level experience raise applicant competition.
Requires manufacturing, HSE, and supply chain domain expertise, reducing cross-industry transferability.
Mandatory ML/AI deployment skills, analytics platforms, and manufacturing domain expertise enforce strict filtering.
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Solve complex analytical problems by researching, designing, implementing, and validating algorithms using statistical and predictive modeling.
Partner with domain experts and solution architects to enable data flow, rapid prototyping, and application of analytical products.
Develop, deploy, and manage enterprise-wide AI/ML/gen-AI digital solutions across Manufacturing, HSE, Supply Chain, and Finance domains.
Intermediate experience with complex business systems and large data sets; demonstrated track record in data science solutions.
Proficiency in analytics platforms like Databricks, Palantir, Snowflake.
Prior experience in full lifecycle development and deployment of AI/ML/gen-AI enterprise digital solutions.
Domain expertise in Manufacturing operations, HSE, Supply chain, and Finance.
Experienced in building analytical solutions with knowledge of big data, open source tools, and clustered cloud compute environments such as Azure or AWS.
Able to collaborate with domain experts and technical teams to translate business requirements into data science models and products.
Familiar with Agile development, CI/CD, AI/ML model validation, and enterprise solution lifecycle management.