Serve as the Subject Matter Expert for various teams to provide support for A/B test design and analysis, as well as data-driven insights through ad-hoc analyses, presentations, and automated reports and dashboards. Mentor junior data scientists on customer behavior and business performance. Oversee junior data scientists in the building of models to better understand the value and churn behavior of our users. Evaluate data patterns and communicate insights and opportunities with executives and other internal teams. Perform ongoing and ad-hoc analyses to evaluate A/B tests, build reporting infrastructure, and provide analytics insights to optimize on app’s Trust and Safety environment and authentication funnels. Work closely with product and engineering teams to develop and deploy robust discovery process for users including relevant recommendation engines. Responsible for discovery and recommendation engine roadmap alignment with product and brand specific goals related to monetization, retention and engagement. Liaise with technical centers of excellence including ML (machine learning) and AI (artificial intelligence) to integrate leading edge technologies into brand specific recommendation systems. Support cross brand initiatives to drive by way of product integrations or transferring successful features specifically on discovery. Stay abreast of latest industry developments related to recommendation engine and propose architectural/technological/process improvements to incumbent solutions within the product. Oversee the integration of captured event data with other sources of customer data, including surveys, ad publishers, and app store data. Use strong communication skills (verbal and written) to manage the support of reporting and business intelligence needs for Product, Marketing, Engineering, and Finance teams. Position allows telecommuting from anywhere in the U.S. Salary: $140,109 - $150,000 per year.
MINIMUM REQUIREMENTS: Bachelor’s degree or U.S. equivalent in Computer Science, Data Science, Business Analytics, Quantitative Methods, Operations Research, Statistics, or a related field, plus 5 years of professional experience as Data Scientist or any occupation/position/job title involving data analysis and testing.
In lieu of a Bachelor's degree plus 5 years of experience, the employer will accept a Master's degree or U.S. equivalent in Computer Science, Data Science, Business Analytics, Quantitative Methods, Operations Research, Statistics or related field, plus 3 years of professional experience as Data Scientist or any occupation/position/job title involving data analysis and testing.
Must also have experience in the following: 3 years of professional experience providing data wrangling services to make data consumable for downstream purposes (including applications or analytics) to interpret themes from quantitative and qualitative data to deliver data-driven insights to optimize growth;
3 years of professional experience using scripting languages (including Python, NumPy, or PANDAS) and structured query language (SQL); 3 years of professional experience with Microsoft Excel and Microsoft PowerPoint to create presentations, and automated reports and dashboards; 3 years of professional experience utilizing machine learning/statistical modeling data analysis tools and techniques (including sklearn, tensorflow, or keras), and parameters that affect their performance; 2 years of professional experience working with Product, Marketing, and Engineering teams; 2 years of professional experience developing and working with recommendation engines; 1 year of professional experience using experimentation on Trust and Safety identity features and working with common KPIs, metrics, and Trust and Safety experiments; and 1 year of professional experience designing and analyzing A/B test for software systems or applications and using statistical methods for experimental design and analysis.
CONTACT: Send resume to lauren.lozano@match.com. Specify ad code AMLL.
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