Data Science Manager

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Amazon is faced with one of the largest, most complex supply chains in the world; the people supply chain. Every year Amazon continues to invest in new buildings to get closer to the customer around the world. This role will unblock Amazon's people growth while bringing the voice of the candidate top of mind to the hiring process.

We are seeking a Data Science Manager to support our Workforce Intelligence Product organization in building science-driven products and tools for Amazon’s Workforce Staffing (WFS) as it scales to becoming one of the largest staffing organizations in the world. WFS is tasked with staffing hourly associates across thousands of global locations to meet the customer delivery promise, but must do so by placing the right candidate in the right role at the right time. This role will facilitate that at scale by leveraging cutting edge algorithms, predictive and prescriptive models as well as required data models to proactively deliver insights and recommendations that optimize our Tier One hiring process.

The ideal candidate will be well-versed in quantitative methods, including classical statistics and machine learning approaches. You will be comfortable combing through computational models, analyzing large scale candidate/associate data and be strategic to provide the best candidate hiring experience to WFS warehouse associate candidates, and optimal hiring outcomes to our various Amazon business lines. The Data Science Manager will play an active role in translating business and functional requirements into concrete deliverables and working closely with the product and engineering teams to deploy solutions into production. You will have the opportunity to work on substantial hiring funnel optimization and forecasting problems and will build a team that conducts research, experiments, prototyping, and deploys models to production to drive business value. As the single-threaded Science leader on the Product team – you will hire, coach, and lead your team of data scientists to develop innovative models that surface actionable insights.

Key Responsibilities Include:

• Build at-scale high performing predictive and prescriptive models and algorithms to personalize the 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 impact of WFS decisions on candidate hiring experiences including funnel fallout rate, attrition, attendance, overtime and more.
• Build various simulation scenarios and guide WFS leadership by enabling candidate's Insights-to-Action and democratizing candidate insights across various candidate communication channels
• Be a storyteller and communicate the needs of candidates, associates and staffing coordinators to WFS stakeholders using candidate insight
• Server as a subject matter expert for design and implementation of high performing algorithms, provide guidance on programmatic integration of candidate insights into labor planning and staffing systems.
• Hire, mentor and lead a team of talented Science professionals (PhD and/or MS in Statistics, AI or Machine Learning)
• Work collaboratively and effectively with engineering and business partners to build algorithms and models for hiring funnel forecasting and optimization.
• Develop mechanisms to audit the forecast quality and develop best practices.
• Apply business judgement to identify opportunities and establish a Science vision for the team, iteratively delivering on the science roadmap in partnership with product and engineering stakeholders.
• Communicate scientific solution and insights effectively to a non-scientific audience.

BASIC QUALIFICATIONS

• Masters degree in Computer Science, Artificial Intelligence, Industrial and Systems Engineering, Statistics, Data Science, Operations Research or other related field.
• 7+ years of relevant work experience in a Data Science and/or Machine Learning role with significant year-over-year responsibility increase.
• 5+ years of experience managing data professionals (data engineers or business intelligence engineers), machine learning scientists, data scientists, research scientists, applied scientists, and/or economists.
• Experience hiring and leading experienced scientists as well as a successful record of developing junior members to a successful career track.
• Several years of experience leading analytical teams and a track record of developing teams to produce successful Data Science solutions that deliver significant benefit to business
• Demonstrated leadership in designing and building at-scale high performing predictive/prescriptive models and algorithms with high positive impact on business outcomes.
• Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, that have been successfully integrated in production systems or informed policy decisions.
• Demonstrable expertise in research design methodologies (e.g., experiments, quasi-experiments, surveys, sampling methods, etc).
• 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
• Proven experience with cross-functional project management.
• Track record of managing multiple projects simultaneously in a fast-paced environment.
• Proven ability to develop engaging customer-facing solutions.
• Ability to self-direct, multitask, and prioritize a constantly evolving workload.
• Ability to travel up to 10%.

PREFERRED QUALIFICATIONS

• A PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent).
• 10+ years of experience working in data science.
• Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.
• Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes.
• Excellent verbal and written communication skills, ability to convey rigorous mathematical and statistical concepts and considerations to non-experts.
• Extensive experience with GPU model training, Unsupervised/Supervised, multivariate at-scale testing and feature engineering algorithms.
• Familiarity with Service Oriented Architecture and designing MicroServices/MicroDBs.
• Familiarity with Amazon's cloud infrastructure including EC2, S3, Sagemaker and Redshift.
• Strong negotiation/relationship building skills.
• Business consulting experience.
• Publications or presentation in recognized Machine Learning or Statistical journals/conferences.
• Excellent organizational skills, time management, and program management skills.
• 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, visit https://www.amazon.jobs/en/disability/us .