• Be thorough in the theory of image processing and computer vision: Image processing, Image annotation and transformations, optimization and estimation, significant point detection and image descriptors. • Build and deploy computer vision solutions either on the edge or cloud. • Experiment with new machine learning algorithms suitable for the business use cases. • Analyze the performance of models and related business metrics and provide insights. • Understand client’s business to be able to articulate the business problem, create relevant solutions using technical knowledge and deploy the solutions to drive revenue. • Optimize and tune the solutions/models for the client context. • Communicate with end clients on solutions, recommendations and performance. • Collaborate and work closely with several key stakeholders (account, engineering, and product and R&D managers) to drive revenue.

Role DescriptionWe'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 Preferred Qualifications - Product analytics experience in a SAAS company - Masters’ or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field Compensation US Zone 1 This role is not available in Zone 1 US Zone 2 $149,200—$201,800 USD US Zone 3 $132,600—$179,400 USD

Role DescriptionWe'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 Preferred Qualifications - Product analytics experience in a SAAS company - Masters’ or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field Compensation

• 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