Data Science Manager
Coinbase
Data Science Manager
Job Description
Responsibilities
- Lead, mentor, and grow a high-performing data science team focused on customer service excellence, including data scientists and data engineers.
- Partner with CX leadership, Product, and Engineering to proactively identify, measuring, and reducing friction points across the customer lifecycle.
- Establish and own business metrics for customer support optimization
- Develop real-time logging and prediction systems that assess session quality and enable proactive user interventions before support contact occurs.
- Build standardized processes for experimentation and optimization, integrating with experimentation platforms to run and measure experiments in self-service, automation, and human resolution strategies.
- Partner with product teams to close the loop—delivering actionable root cause analyses, mapping issues to responsible owners, and providing cost breakdowns per issue to inform prioritization.
- Design anomaly detection systems across self-help and automation channels to trigger escalation pathways and prevent degradation of service quality.
- Champion a culture of rigorous, data-driven decision making in CX, with clear reporting, alerting, and accountability mechanisms for issue owners and product DRIs.
- Communicate insights and recommendations to senior Coinbase leadership, transforming quantitative findings into compelling narratives that influence company strategy.
- Drive organizational initiatives to scale customer experience analytics through better systems, automation, and governance.
Required Qualifications
- BA / BS degree business, computer science, statistics, applied mathematics, or any scientific or computational degree
- 8+ years of experience in data science, analytics, or a related field, with at least 3+ years managing high-performing teams.
- Demonstrated experience in leading end-to-end measurement and optimization frameworks across multiple product or operational contexts.
- Strong background in machine learning, experimentation, and statistical analysis applied to product, customer experience, or operations.
- Proven ability to partner cross-functionally with Product, Engineering, and Operations to deliver measurable business impact.
- Experience designing and implementing real-time analytics, anomaly detection, and automated intervention systems.
- Exceptional communication skills, with the ability to synthesize complex data into clear, actionable strategies for executives and cross-functional partners.
- Comfortable with ambiguity and adept at defining structure in complex, multi-stakeholder projects.
- Deep focus on scalability — building common tooling and frameworks that can be used across multiple teams and contexts.
- Familiarity with LLM or NLP-based classification tools, predictive modeling, and event logging systems a plus.
- Passion for delivering delightful customer experiences and driving measurable reductions in churn and operational costs.
Preferred Qualifications
- Masters or PhD in business, computer science, statistics, applied mathematics, or any scientific or computational degree
- Prior data science experience / domain expertise in the customer support area
- Deep knowledge of causal inference techniques is a plus
Required Skills
- data science
- analytics
- machine learning
- experimentation
- statistical analysis
- real-time analytics
- anomaly detection
- automated intervention systems
- communication skills
- cross-functional partnership
- LLM or NLP-based classification tools
- predictive modeling
- event logging systems
- causal inference techniques
Benefits
- bonus eligibility
- benefits (including medical, dental, vision and 401(k))
Salary Range
$207485 - $244100 USD
Locations
- US Zone 1 (Job Requisitions Only), United States (Remote)
Salary
207,485 - 244,100 USD / yearly
Skills Required
- data scienceintermediate
- analyticsintermediate
- machine learningintermediate
- experimentationintermediate
- statistical analysisintermediate
- real-time analyticsintermediate
- anomaly detectionintermediate
- automated intervention systemsintermediate
- communication skillsintermediate
- cross-functional partnershipintermediate
- LLM or NLP-based classification toolsintermediate
- predictive modelingintermediate
- event logging systemsintermediate
- causal inference techniquesintermediate
Required Qualifications
- BA / BS degree business, computer science, statistics, applied mathematics, or any scientific or computational degree (experience)
- 8+ years of experience in data science, analytics, or a related field, with at least 3+ years managing high-performing teams. (experience)
- Demonstrated experience in leading end-to-end measurement and optimization frameworks across multiple product or operational contexts. (experience)
- Strong background in machine learning, experimentation, and statistical analysis applied to product, customer experience, or operations. (experience)
- Proven ability to partner cross-functionally with Product, Engineering, and Operations to deliver measurable business impact. (experience)
- Experience designing and implementing real-time analytics, anomaly detection, and automated intervention systems. (experience)
- Exceptional communication skills, with the ability to synthesize complex data into clear, actionable strategies for executives and cross-functional partners. (experience)
- Comfortable with ambiguity and adept at defining structure in complex, multi-stakeholder projects. (experience)
- Deep focus on scalability — building common tooling and frameworks that can be used across multiple teams and contexts. (experience)
- Familiarity with LLM or NLP-based classification tools, predictive modeling, and event logging systems a plus. (experience)
- Passion for delivering delightful customer experiences and driving measurable reductions in churn and operational costs. (experience)
Preferred Qualifications
- Masters or PhD in business, computer science, statistics, applied mathematics, or any scientific or computational degree (experience)
- Prior data science experience / domain expertise in the customer support area (experience)
- Deep knowledge of causal inference techniques is a plus (experience)
Responsibilities
- Lead, mentor, and grow a high-performing data science team focused on customer service excellence, including data scientists and data engineers.
- Partner with CX leadership, Product, and Engineering to proactively identify, measuring, and reducing friction points across the customer lifecycle.
- Establish and own business metrics for customer support optimization
- Develop real-time logging and prediction systems that assess session quality and enable proactive user interventions before support contact occurs.
- Build standardized processes for experimentation and optimization, integrating with experimentation platforms to run and measure experiments in self-service, automation, and human resolution strategies.
- Partner with product teams to close the loop—delivering actionable root cause analyses, mapping issues to responsible owners, and providing cost breakdowns per issue to inform prioritization.
- Design anomaly detection systems across self-help and automation channels to trigger escalation pathways and prevent degradation of service quality.
- Champion a culture of rigorous, data-driven decision making in CX, with clear reporting, alerting, and accountability mechanisms for issue owners and product DRIs.
- Communicate insights and recommendations to senior Coinbase leadership, transforming quantitative findings into compelling narratives that influence company strategy.
- Drive organizational initiatives to scale customer experience analytics through better systems, automation, and governance.
Benefits
- general: bonus eligibility
- general: benefits (including medical, dental, vision and 401(k))
Tags & Categories
Data Science Manager
Coinbase
Data Science Manager
Job Description
Responsibilities
- Lead, mentor, and grow a high-performing data science team focused on customer service excellence, including data scientists and data engineers.
- Partner with CX leadership, Product, and Engineering to proactively identify, measuring, and reducing friction points across the customer lifecycle.
- Establish and own business metrics for customer support optimization
- Develop real-time logging and prediction systems that assess session quality and enable proactive user interventions before support contact occurs.
- Build standardized processes for experimentation and optimization, integrating with experimentation platforms to run and measure experiments in self-service, automation, and human resolution strategies.
- Partner with product teams to close the loop—delivering actionable root cause analyses, mapping issues to responsible owners, and providing cost breakdowns per issue to inform prioritization.
- Design anomaly detection systems across self-help and automation channels to trigger escalation pathways and prevent degradation of service quality.
- Champion a culture of rigorous, data-driven decision making in CX, with clear reporting, alerting, and accountability mechanisms for issue owners and product DRIs.
- Communicate insights and recommendations to senior Coinbase leadership, transforming quantitative findings into compelling narratives that influence company strategy.
- Drive organizational initiatives to scale customer experience analytics through better systems, automation, and governance.
Required Qualifications
- BA / BS degree business, computer science, statistics, applied mathematics, or any scientific or computational degree
- 8+ years of experience in data science, analytics, or a related field, with at least 3+ years managing high-performing teams.
- Demonstrated experience in leading end-to-end measurement and optimization frameworks across multiple product or operational contexts.
- Strong background in machine learning, experimentation, and statistical analysis applied to product, customer experience, or operations.
- Proven ability to partner cross-functionally with Product, Engineering, and Operations to deliver measurable business impact.
- Experience designing and implementing real-time analytics, anomaly detection, and automated intervention systems.
- Exceptional communication skills, with the ability to synthesize complex data into clear, actionable strategies for executives and cross-functional partners.
- Comfortable with ambiguity and adept at defining structure in complex, multi-stakeholder projects.
- Deep focus on scalability — building common tooling and frameworks that can be used across multiple teams and contexts.
- Familiarity with LLM or NLP-based classification tools, predictive modeling, and event logging systems a plus.
- Passion for delivering delightful customer experiences and driving measurable reductions in churn and operational costs.
Preferred Qualifications
- Masters or PhD in business, computer science, statistics, applied mathematics, or any scientific or computational degree
- Prior data science experience / domain expertise in the customer support area
- Deep knowledge of causal inference techniques is a plus
Required Skills
- data science
- analytics
- machine learning
- experimentation
- statistical analysis
- real-time analytics
- anomaly detection
- automated intervention systems
- communication skills
- cross-functional partnership
- LLM or NLP-based classification tools
- predictive modeling
- event logging systems
- causal inference techniques
Benefits
- bonus eligibility
- benefits (including medical, dental, vision and 401(k))
Salary Range
$207485 - $244100 USD
Locations
- US Zone 1 (Job Requisitions Only), United States (Remote)
Salary
207,485 - 244,100 USD / yearly
Skills Required
- data scienceintermediate
- analyticsintermediate
- machine learningintermediate
- experimentationintermediate
- statistical analysisintermediate
- real-time analyticsintermediate
- anomaly detectionintermediate
- automated intervention systemsintermediate
- communication skillsintermediate
- cross-functional partnershipintermediate
- LLM or NLP-based classification toolsintermediate
- predictive modelingintermediate
- event logging systemsintermediate
- causal inference techniquesintermediate
Required Qualifications
- BA / BS degree business, computer science, statistics, applied mathematics, or any scientific or computational degree (experience)
- 8+ years of experience in data science, analytics, or a related field, with at least 3+ years managing high-performing teams. (experience)
- Demonstrated experience in leading end-to-end measurement and optimization frameworks across multiple product or operational contexts. (experience)
- Strong background in machine learning, experimentation, and statistical analysis applied to product, customer experience, or operations. (experience)
- Proven ability to partner cross-functionally with Product, Engineering, and Operations to deliver measurable business impact. (experience)
- Experience designing and implementing real-time analytics, anomaly detection, and automated intervention systems. (experience)
- Exceptional communication skills, with the ability to synthesize complex data into clear, actionable strategies for executives and cross-functional partners. (experience)
- Comfortable with ambiguity and adept at defining structure in complex, multi-stakeholder projects. (experience)
- Deep focus on scalability — building common tooling and frameworks that can be used across multiple teams and contexts. (experience)
- Familiarity with LLM or NLP-based classification tools, predictive modeling, and event logging systems a plus. (experience)
- Passion for delivering delightful customer experiences and driving measurable reductions in churn and operational costs. (experience)
Preferred Qualifications
- Masters or PhD in business, computer science, statistics, applied mathematics, or any scientific or computational degree (experience)
- Prior data science experience / domain expertise in the customer support area (experience)
- Deep knowledge of causal inference techniques is a plus (experience)
Responsibilities
- Lead, mentor, and grow a high-performing data science team focused on customer service excellence, including data scientists and data engineers.
- Partner with CX leadership, Product, and Engineering to proactively identify, measuring, and reducing friction points across the customer lifecycle.
- Establish and own business metrics for customer support optimization
- Develop real-time logging and prediction systems that assess session quality and enable proactive user interventions before support contact occurs.
- Build standardized processes for experimentation and optimization, integrating with experimentation platforms to run and measure experiments in self-service, automation, and human resolution strategies.
- Partner with product teams to close the loop—delivering actionable root cause analyses, mapping issues to responsible owners, and providing cost breakdowns per issue to inform prioritization.
- Design anomaly detection systems across self-help and automation channels to trigger escalation pathways and prevent degradation of service quality.
- Champion a culture of rigorous, data-driven decision making in CX, with clear reporting, alerting, and accountability mechanisms for issue owners and product DRIs.
- Communicate insights and recommendations to senior Coinbase leadership, transforming quantitative findings into compelling narratives that influence company strategy.
- Drive organizational initiatives to scale customer experience analytics through better systems, automation, and governance.
Benefits
- general: bonus eligibility
- general: benefits (including medical, dental, vision and 401(k))
Tags & Categories