Amazon’s mission is to be the most customer centric company in the world. The Workforce Staffing (WFS) organization is on the front line of that mission by hiring the hourly fulfillment associates who make that mission a reality. To drive the necessary growth and continued scale of Amazon’s associate needs within a constrained employment environment, Amazon has created the Workforce Intelligence (WFI) team. This team will (re)invent how Amazon attracts, communicates with, and ultimately hires its hourly associates. This team owns multi-layered research and program implementation to drive deep learning, process improvements, and strategic recommendations to global leadership.
Are you passionate about data? Do you enjoy questioning the status quo? Do complex and difficult challenges excite you? If yes, this may be the team for you.
The Data Scientist will be responsible for creating cutting edge algorithms, predictive and prescriptive models as well as required data models to facilitate WFS at-scale warehouse associate hiring. This role acts as an internal consultant to the Planing and Forecasting (PAF) team covering responsibilities such as at-scale hiring process improvement, analyzing large scale candidate/associate data and being strategic to providing best candidate hiring experience to WFS warehouse associate candidates.
· Build at-scale high performing predictive and prescriptive models and algorithms to personalize candidate hiring experience
· Provide Next-Best-Actions (NBAs) and Next-Best-Offers to all WFS candidates using hiring funnel and application datasets
· Define, create and invent metrics and Key Performance Identifiers (KPIs) to measure the impacts of WFS decisions on candidate hiring experiences including funnel fallout rate, attrition, attendance, overtime and etc
· Build various simulation scenarios and guide WFS leadership by enabling candidate's Insights-to-Action and democratizing candidate insights across various candidate communication channel
· Be a storyteller and communicate the needs of candidates, associates and staffing coordinators to WFS stakeholders using candidate insight
· Act as a mentor to less tenured engineers within the team, be a subject matter for design and implementation of high performing algorithms, provide guidance on programmatic integration of candidate insights into labor planning systems
Inclusive Team Culture
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have 12 affinity groups (employee resource groups) with more than 87,000 employees across hundreds of chapters around the world. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which reminds team members to seek diverse perspectives, learn and be curious, and earn trust.
It isn’t about which hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We offer flexibility and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
We care about your career growth too. Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it.
· Masters degree in Computer Science, Artificial Intelligence, Industrial and Systems Engineering or Operations Research
· Minimum 3+ years of relevant work experience in a Data Science and/or Machine Learning role
· Demonstrated leadership in designing and building at-scale high performing predictive/prescriptive models and algorithms
· Strong knowledge of scripting languages such as Python and R
· Strong knowledge of SQL, NoSQL, Spark and/or Scala
· Ability to turn complex problems into simple solutions
· Track record of managing multiple projects simultaneously in a fast-paced environment
· Proven ability to develop engaging customer-facing products
· Ability to self-direct, multitask, and prioritize a constantly evolving workload
· Extensive experience with Python Machine Learning libraries such as Numpy, SciPy, Scikit-learn, CUDA and PyTorch
· Extensive experience with GPU model training, Unsupervised/Supervised, multivariate at-scale testing and feature engineering algorithms
· Familiarity with Service Oriented Architecture (SoA) and designing MicroServices/MicroDBs
· Familiarity with Amazon's cloud infrastructure including EC2, S3 and Redshift
· Ability to work cross functionally
· Strong negotiation/relationship building skills
· Business consulting experience
· Ability to work on a diverse team or with a diverse range of coworkers
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
We believe passionately that employing a diverse workforce is central to our success and we make recruiting decisions based on your experience and skills. We welcome applications from all members of society irrespective of age, gender, disability, sexual orientation, race, religion or belief.