Senior Data Scientist

Posted 2 months agoViewed
150000 - 180000 USD per year
U.S.Full-TimeSoftware Development
Company:Gladly
Location:U.S.
Languages:English
Seniority level:Senior, 5+ years
Experience:5+ years
Skills:
PythonSQLArtificial IntelligenceData AnalysisMachine LearningProduct AnalyticsData scienceMentoring
Requirements:
5+ years of experience working with data to solve problems and make decisions, especially as a data scientist or product analyst A strong track record of designing, prototyping, scaling and launching data science products to solve business problems Excellent SQL and python skills for data manipulation, exploration and visualization, especially in Jupyter notebooks A strong understanding of ML algorithms Excellent communication skills; you excel at turning data into compelling and actionable insights and have a proven track record for driving change in a product organization Customer-centricity and product focus. You look at everything you create through the lens of how it improves experience for the end-user. You are comfortable communicating how various approaches might impact the product behavior (and vice versa). Learning mentality. You aren't intimidated by new domains or technology; you're willing to dive into documentation/videos, talk to your teammates, and experiment to become well-versed. Experience working with cross-functional teams including but not limited to Engineering, Design and Product.
Responsibilities:
Collaborate with various Gladly teams and stakeholders to build a deep understanding of our business, our customers and the problems they face Work closely with our product leadership to influence product roadmap and strategy, driving collaborative discussions based on quantitative insights Design and perform analyses or experiments to deepen our understanding of customers, uncover product improvement opportunities, provide actionable recommendations, and drive product decisions Develop novel algorithms to improve customer service automation and Hero efficiency, working on problems from conception through design, prototyping and shipping production features Provide guidance to other teams about the best practices for gaining insight into product behavior and experimentation to improve product effectiveness Provide mentorship to other data scientists through code and research reviews, documentation, technical guidance and pairing
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