Data Scientist
The Device, Digital & Alexa Support (D2AS) team seeks a Data Scientist to drive our hiring process improvements. In this role, you will:- Lead modeling projects to enhance our hiring pipeline efficiency and candidate experience.- Develop data-driven insights to inform product decisions.- Design and conduct statistical experiments to uncover hiring optimization opportunities.- Create user-friendly analytical tools for our product team.The ideal candidate will have:- Strong leadership and project management skills.- Experience in data requirements gathering and statistical methodology development. - Ability to balance technical expertise with business acumen - Creativity in problem-solving, backed by statistical evidence.Your work will directly impact our ability to attract and retain top talent, ultimately benefiting our customers through improved support services. Join us in simplifying and enhancing our hiring process with data-driven solutions.Key job responsibilities- Design and run experiments, research new algorithms, and find new ways to improve hiring analytics to optimize the candidate and associate experience. - Research machine learning algorithms and implement by tailoring to business needs and test on large datasets. - Partner with scientists, engineers and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. - Collaborate with BI/Data Engineer teams and drive the collection of new data and the refinement of existing data sources to continually improve data quality. - Foster culture of continuous engineering improvement through mentoring, feedback, and metrics. - Manipulating/mining data from databases (Redshift, SQL Server, Oracle DW, and Salesforce). - Providing analytical network support to improve quality and standard work results.A day in the lifeWe thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment.If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!Benefits summary: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) PlanAbout the teamWe at D2AS strive to make digital experiences effortless for customers. Our goal is to anticipate, evaluate, prevent, and eliminate any effort required from customers. We achieve this by setting the strategy for digital support and accelerating the delivery of seamless support experiences across Amazon's digital products.Our team combines strategic thinking, technology expertise, and customer experience best practices. This ensures customers can easily get the most value from Amazon's digital offerings. We focus on providing the right support at the right time, tailored to each customer's needs. By eliminating friction and making support effortless, we enhance the overall customer experience.BASIC QUALIFICATIONS- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...