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Mid-level generalist ML title, metro hiring, and recognizable brand drive high competition.
CPG-focused forecasting, pricing and MMM increase domain specificity, making background fit moderately sensitive.
Explicit 4-6 years and mandatory ML, Python, and modeling skills make shortlisting strict.
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Develop and deploy machine learning models for business problems like demand forecasting, price optimization, and operational analytics to drive measurable business outcomes.
Engineer features from diverse data sources, including external datasets, for scalable and repeatable data science solutions.
Collaborate cross-functionally and contribute to developing data science standards, tools, and innovation accelerators within the team.
Bachelor's degree in Technology/Engineering/Science mandatory.
4-6 years of analytics experience with supervised machine learning.
Experience with Agile development methodology and technical use of cloud platforms (e.g., Google Cloud Platform preferred).
Proficiency in Python, exploratory data analysis, inferential statistics, plus experience in at least two of: predictive modeling, forecasting, market mix modeling, Bayesian methods, linear or network optimization.
Experienced data scientist able to balance technical model development with business problem framing and storytelling to varied audiences.
Comfortable in collaborative, agile environments requiring cross-disciplinary coordination and automation solutioning.
Skilled in cloud data platforms and a variety of analytics tools with a bias towards innovation and establishing best practices.