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Senior Data Science Manager

Posted 9 days agoViewed

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💎 Seniority level: Manager, 7+ years

📍 Location: United States, EU

💸 Salary: 161000.0 - 224000.0 USD per year

🏢 Company: Taskrabbit👥 251-500💰 Secondary Market over 9 years agoMarketplaceE-CommerceJanitorial ServiceFacilities Support ServicesFreight ServicePeer to PeerSharing Economy

⏳ Experience: 7+ years

🪄 Skills: AWSLeadershipPythonSQLGCPMachine LearningPeople ManagementData scienceSparkCommunication SkillsData visualizationTeam managementStakeholder managementStrategic thinkingData modelingData analyticsData managementA/B testing

Requirements:
  • 7+ years of experience in data science, analytics, or a related quantitative field, with a proven track record of delivering impactful results.
  • 3+ years of leadership experience, managing and scaling high-performance data science/analytics teams (5+ direct reports preferred).
  • Strong technical expertise in statistical methods, experiment design, and machine learning, with proficiency in SQL and at least one programming language (Python, R).
  • Experience with modern data platforms (AWS, GCP, Spark) and BI tools (Looker, Tableau) to support scalable analytics.
  • Exceptional communication and stakeholder management skills, with the ability to translate complex data insights into clear, actionable recommendations for diverse audiences, including executives.
  • Strategic mindset and business acumen, with a history of guiding data-driven product innovation and aligning initiatives with company goals.
  • Proven ability to influence cross-functional teams and drive alignment in a fast-paced environment, shaping product roadmaps through data-backed narratives.
Responsibilities:
  • Drive data-informed decision-making by synthesizing key insights that influence product roadmaps and strategic initiatives.
  • Serve as a trusted advisor to Product, Engineering, Design, Marketing, and Operations, translating complex analyses into actionable recommendations.
  • Define the long-term strategy for Taskrabbit’s Data Science organization, ensuring alignment with business objectives.
  • Hire, develop, and mentor a high-performing, diverse team of data scientists and analysts.
  • Lead the development and adoption of robust experimentation frameworks (A/B testing, multi-variant testing) to drive data-driven product improvements.
  • Partner with Engineering to build and maintain scalable data infrastructure that powers advanced analytics and research.
  • Balance short-term execution with long-term innovation, consistently measuring and reporting on the ROI of data science initiatives.
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