Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies for Dash Chat and Search
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritize ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction  
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies for Dash Chat and Search
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritize ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction  
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

Role Description

Responsibilities

• Help define company data assets (data model), Spark, SparkSQL jobs to populate data models
• Help define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage
• Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable 
• Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
• Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
• Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• 5+ years of Spark, Python, Java, C++, or Scala development experience
• 5+ years of SQL experience
• 5+ years of experience with schema design, dimensional data modeling, and medallion architectures
• Experience with the Databricks platform and data lake architectures for large-scale data processing and analytics
• Excellent product strategic thinking and communications to influence product and cross-functional teams by identifying the data opportunities to drive impact
• BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
• Experience designing, building and maintaining data processing systems

Role Description

Responsibilities

• Help define company data assets (data model), Spark, SparkSQL jobs to populate data models
• Help define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage
• Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable 
• Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
• Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
• Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• 5+ years of Spark, Python, Java, C++, or Scala development experience
• 5+ years of SQL experience
• 5+ years of experience with schema design, dimensional data modeling, and medallion architectures
• Experience with the Databricks platform and data lake architectures for large-scale data processing and analytics
• Excellent product strategic thinking and communications to influence product and cross-functional teams by identifying the data opportunities to drive impact
• BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
• Experience designing, building and maintaining data processing systems

Role Description

Dropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that span multiple lines of business while driving standardization in how we build, deploy, and govern analytics pipelines across Dropbox.

This is not a maintenance role. We are modernizing our analytics platform, upgrading orchestration infrastructure, building shared and reusable data models with conformed dimensions, establishing a certified metrics framework, and laying the foundation for AI-native data development. You will partner closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams to make this happen.

You will play a crucial role in establishing analytics engineering standards, designing scalable data models, and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership, shape the technical direction of analytics infrastructure at Dropbox, and directly influence how data powers product and business decisions.

Responsibilities

• Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions
• Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards
• Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access
• Architect and implement a shift-left data governance strategy,  working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production
• Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement
• Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable
• Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development

On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.

Requirements

• BS degree in Computer Science or related technical field, or equivalent technical experience
• 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership
• 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL)
• 8+ years of Python development experience, including building and maintaining production data pipelines
• Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains
• Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns
• Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries

Preferred Qualifications

• Experience with Databricks (Unity Catalog, Delta Lake) and modern lakehouse architectures
• Experience leading orchestration or platform modernization efforts at scale
• Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, Databricks Metric Views, or equivalent)
• Track record of establishing data engineering standards and best practices in a federated analytics organization

Role Description

Dropbox is looking for a Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. In this role you will build large, scalable analytics pipelines using modern data technologies. This is not a “maintain existing platform” or “make minor tweaks to current code base” kind of role. We are effectively building from the ground up and plan to leverage the most recent Big Data technologies. If you enjoy building new things without being constrained by technical debt, this is the job for you!

Responsibilities

• Define company data assets (data model), Spark, SparkSQL jobs to populate data models
• Define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage
• Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable 
• Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
• Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
• Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts

On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.

Requirements

• 5+ years of Spark, Python, Java, C++, or Scala development experience
• 5+ years of SQL experience
• 5+ years of experience with schema design, dimensional data modeling, and medallion architectures
• Experience with the Databricks platform and data lake architectures for large-scale data processing and analytics
• Excellent product strategic thinking and communications to influence product and cross-functional teams by identifying the data opportunities to drive impact
• BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
• Experience designing, building and maintaining data processing systems

Preferred Qualifications

• 7+ years of SQL experience 
• 7+ years of experience with schema design, dimensional data modeling, and medallion architectures
• Experience with Airflow or other similar orchestration frameworks
• Experience building data quality monitoring using MonteCarlo or similar tools

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritize ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction  
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritize ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction  
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As the Sr Data Science Manager for Dash Experience, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with the Head of Data Science and Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Manage and scale a high performing team of data scientists
• Coach and mentor data scientists of varying experiences to ensure their continued growth 
• Plan, execute, and deliver a profolio of mission-critical data science projects for Dash Experience, and provide technical leadership in a fast-paced environment
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate
• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Identify what matters most and prioritize ruthlessly

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 10+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• 3+ years of experience directly managing data scientists or product analysts
• Proven track record of managing a portfolio of Data Science projects that improve user experience and drive measurable business impact
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques
• Experience using data to inform product and business decisions that led to measurable outcomes
• Exceptional verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Compensation

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As the Sr Data Science Manager for Dash Experience, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with the Head of Data Science and Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Manage and scale a high performing team of data scientists
• Coach and mentor data scientists of varying experiences to ensure their continued growth 
• Plan, execute, and deliver a profolio of mission-critical data science projects for Dash Experience, and provide technical leadership in a fast-paced environment
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate
• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Identify what matters most and prioritize ruthlessly 

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 10+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• 3+ years of experience directly managing data scientists or product analysts
• Proven track record of managing a portfolio of Data Science projects that improve user experience and drive measurable business impact
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques
• Experience using data to inform product and business decisions that led to measurable outcomes
• Exceptional verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product