With over 120 million members, Goodreads is the world’s largest site for readers and book recommendations. Our mission is to help people find and share books they love. Loved by avid and casual readers alike, Goodreads members can discover new books by seeing what their friends are reading or by using the Goodreads Book Recommendation Engine, share ratings and recommendations, track what they have read, and list what they want to read. Goodreads is also a place where more than 220,000 authors connect with readers. Come join us and be a part of Amazon family here at Goodreads!
You will be on a dynamic team that works on a broad range of projects which impact the business as well as Goodreads community. As a team, we power and help optimize Goodreads experiences and features. We investigate feature performance, user behavior, trends and offer insightful recommendations, analytical and data science solutions to the business. We are responsible for reporting and monitoring business metrics and KPIs.
As a Data Scientist you will prototype scalable models and algorithms to meet customer needs. You will be responsible for design and analysis of experiments to evaluate and optimize data science solutions and Goodreads features and experiences. You will build data products to drive value for Amazon. You will create self-serve dashboards and automated reports to increase operational efficiency. You will work with engineers and partner teams to deploy and monitor models and algorithms.
The role will require an end-to-end understanding of data and reporting, and applying a range of data science methodologies and tools combined with subject matter expertise to solve difficult business problems; working with business owners to understand and define their analytics needs; working with data engineering to acquire necessary data; building models, reports and performing analyses to draw insights; and finally working with the appropriate parts of the organization to implement changes based on those insights.
· Understand the Goodreads/Amazon data structures (MySQL/Data Lake/Redshift)
· Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for RedShift and Data Lake storage systems.
· Investigate the feasibility of applying scientific principles and concepts to business problems
· Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies.
· Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing and machine learning algorithms.
· Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators.
· Develop metrics to quantify the benefits of a solution and influence project resources.
· Partner with Engineering/Data Engineering to improve the quality of existing data and bring additional data sources in line
· Audit metric data and measure project progress and success.
· Build/automate reports/dashboards (in Tableau) that allow the business leaders to get a clear snapshot of their operations
· Design and analyze A/B tests to quantify impact of customer-facing changes
· Develop innovative experimental design and measurement methodologies to understand our customer growth and business efficacy
· Participate in discussions, team planning, office hours, and metric reviews
· Design and implement scalable and reliable approaches to support or automate decision making throughout the business.
· Communicate insights to the business partners, Goodreads leadership, and Amazon stakeholders – emphasizing clarity, completeness, and actionability
· BS/BA in quantitative field – Computer Sciences, Math, Statistics or related field.
· 3+ years of professional experience in data science / advanced analytics
· Experience in a business environment with large-scale, complex datasets
· Proficient in SQL and experience with efficient processing of large data sets. Ability to write sophisticated and optimized queries against large databases
· Familiarity with columnar databases like Redshift; Understand database optimization Proficient with math/stats software – R, Python and Tableau – build clear and actionable dashboards
· Experience conveying key insights from complex analysis in summarized business terms
· Modeling – experience building complex models using statistical, ML and forecasting components
· A Graduate degree (MS, MBA, PhD, etc.) in a quantitative field will be highly valued but is not required
· Experience with Big Data solutions as well as other AWS solutions
· Business Acumen – understand business drivers and have a framework-driven process of analyzing business problems and developing solutions
· Communication – share insights in a way that is easy to grasp and actionable and build relationships to help drive adoption of data- and insights-driven decision making
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