Description

　　In Amazon's Workforce Solutions Analytics and Technology Org, we leverage state-of-the-art technologies to address complex human challenges on a grand scale. Our mission is to deliver captivating, user-centric, and personalized experiences that empower employees to effectively manage their work-life balance from anywhere, at any time. The Workforce Solutions team is actively seeking a Senior Data Scientist to lead our data science efforts. This role encompasses a wide array of responsibilities, with a primary focus on Natural Language Processing and machine learning. Your contributions will be instrumental to tackle staffing challenges within Amazon's warehouses.

　　Key job responsibilities

　　As a Senior Data Scientist specialized in Natural Language Processing, you will play a key role in extracting meaningful insights from vast structured and unstructured datasets. Your responsibilities will include:

　　Data Analysis and Modeling:

　　• Leverage advanced statistical and machine learning techniques to analyze large and complex datasets.

　　• Develop and implement NLP models, including Language Models (LLM), to extract insights from unstructured textual data.

　　Problem Solving:

　　• Collaborate with cross-functional teams to identify business problems and develop innovative data-driven solutions.

　　• Address challenges related to scalability, data quality, system integration and ML Ops.

　　Algorithm Development:

　　• Design and implement algorithms to process, analyze, and derive insights from diverse data sources.

　　• Stay current with the latest advancements in NLP and machine learning, applying cutting-edge techniques to solve business problems.

　　Data Visualization and Communication:

　　• Communicate findings effectively to both technical and non-technical stakeholders through compelling data visualizations and presentations.

　　• Collaborate with business teams to understand requirements and translate them into actionable insights.

　　We are open to hiring candidates to work out of one of the following locations:

　　Austin, TX, USA | Nashville, TN, USA | Seattle, WA, USA | Tempe, AZ, USA

　　Basic Qualifications

　　5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

　　4+ years of data scientist experience

　　Experience with statistical models e.g. multinomial logistic regression

　　Master's or Ph.D. in Computer Science, Statistics, Data Science, or a related quantitative field.

　　Proven experience in applying NLP techniques, including working with Language Models (LLM).

　　Strong programming skills in languages such as Python or R.

　　Proficiency in using data analysis and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).

　　Preferred Qualifications

　　Experience as a leader and mentor on a data science team

　　Experience with large-scale data processing and analysis using distributed computing frameworks (e.g., Apache Spark).

　　Experience with cloud computing platforms (e.g., AWS, Azure).

　　Familiarity with big data technologies and tools.

　　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.

　　Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.