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Senior Data Scientist, Business Sales

Posted 2024-08-30

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๐Ÿ’Ž Seniority level: Senior, At least 4 years experience in Sales Optimization Data Science

๐Ÿ“ Location: United States

๐Ÿ” Industry: Advertising

๐Ÿข Company: StackAdapt๐Ÿ‘ฅ 1001-5000๐Ÿ’ฐ $711.6k Series A on 2016-01-28Digital MarketingAdvertisingVideo AdvertisingAdvertising PlatformsAd TargetingMobile AdvertisingMachine LearningMarketingAd Retargeting

๐Ÿ—ฃ๏ธ Languages: English

โณ Experience: At least 4 years experience in Sales Optimization Data Science

๐Ÿช„ Skills: PythonSQLData AnalysisMachine LearningNumpyAlgorithmsData analysisData scienceData StructuresGoPandasCommunication SkillsAnalytical SkillsCollaborationC (Programming language)

Requirements:
  • Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.
  • Have the ability to take an ambiguously defined task, and break it down into actionable steps.
  • At least 4 years experience in Sales Optimization Data Science.
  • Have a comprehensive understanding of statistics, optimization and machine learning.
  • Bring an analytical mind to the work blending data science and internal business operations and analytics.
  • Are proficient in coding, data structures, and algorithms.
  • Enjoy working in a friendly, collaborative environment with others.
Responsibilities:
  • Build predictive and optimization models to guide company resourcing decisions.
  • Build customer acquisition models, that identify high potential customers and their associated values.
  • Make Data Science modeling accessible to non-experts through usage of the right tools for typical prediction tasks.
  • Implement time series forecasting to predict revenue from clients, especially when it is likely to grow or decrease.
  • Write production code, sometimes collaborating with Data Engineers, to implement the novel ML algorithms.
  • Prototype potential algorithms and pipelines, test them using historical data, and iterate to modify based on insights.
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  • Bring an analytical mind to the work blending data science and internal business operations and analytics.
  • Are proficient in coding, data structures, and algorithms.
  • Enjoy working in a friendly, collaborative environment with others.

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  • Build customer acquisition models, that identify high potential customers and their associated values.
  • Make Data Science modeling accessible to non-experts through usage of the right tools for typical prediction tasks.
  • Implement time series forecasting to predict revenue from clients, especially when it is likely to grow or decrease.
  • Write production code, sometimes collaborating with Data Engineers, to implement the novel ML algorithms.
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