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Strong employer brand, hybrid remote, mid-level ML title, and metro location increase applicant density.
Core ML and data science skills transfer broadly, but CRM/revenue-domain experience increases specificity.
Explicit 4–7 years requirement plus mandatory ML, Python, SQL, CRM and deployment skills.
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Develop and deliver predictive models focusing on sales, marketing, and customer success data to enhance operational efficiency and revenue forecasting.
Establish and maintain scalable data pipelines and AI-based validation systems to ensure high-quality, trustworthy business data across sales and marketing functions.
Collaborate cross-functionally with Sales, Marketing Ops, BizTech, and Enablement teams to automate data insights and support GTM execution and strategic planning.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related field.
4 to 7 years of experience in data science, AI engineering, or advanced analytics roles.
Proficiency in Python, SQL, and dashboarding tools like Tableau with experience in ML model deployment for sales/revenue strategies.
Experience working with CRM systems and sales/marketing data pipelines; exposure to LLM-based AI tools for data enrichment or automation.
Experienced in applying AI/ML models and large language models to enhance B2B sales and marketing data accuracy and operational decision-making.
Capable of building scalable data infrastructure and predictive analytics tools to support strategic revenue operations in a hybrid work environment.
Strong business acumen and detail orientation, with the ability to collaborate across multiple functions in physical operations industries like transportation, manufacturing, and field services.