Sr. Data Scientist, Public Sector - AWS Professional Services

US, VA, Virtual Location - Virginia

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Job summary
Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Want to help public sector, medical center and non-profit agencies derive business value through the adoption of Artificial Intelligence (AI)? Eager to learn from many different enterprises' use cases of AWS ML and DL? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology?

At Amazon Web Services (AWS), we are helping large enterprises build ML and DL models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. Our Professional Services organization is a unique consulting team that works closely with our AWS customers to address their business needs using AI.



We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you have experience with AI, building ML or DL models, and want to innovate for our customers in the world of AI, then we’d like to have you join our team. As a Data Scientist, you will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers. A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions.


Major responsibilities include:
  • Understand the customer’s business need and guide them to a solution using our AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances .
  • Assist customers by being able to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.
  • Use Deep Learning frameworks like PyTorch, Tensorflow and MxNet to help our customers build DL models.
  • Use SparkML and Amazon Machine Learning (AML) to help our customers build ML models.
  • Work with our Professional Services Big Data consultants to analyze, extract, normalize, and label relevant data.
  • Work with our Professional Services DevOps consultants to help our customers operationalize models after they are built.
  • Assist customers with identifying model drift and retraining models.
  • Research and implement novel ML and DL approaches, including using FPGA.
  • This position can have periods of up to 10% travel.
  • This position requires that the candidate selected be a US Citizen and obtain and maintain an active TS/SCI security clearance.
  • Location is open - our Data Scientists can be based out of any of our US office locations.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we 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 remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance
Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work.


Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.


Basic Qualifications


• Bachelor’s degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent professional or military experience
• Experience with ML fields, e.g., natural language processing, computer vision, statistical learning theory
• 6+ years of industry experience in predictive modeling, data science, and analysis
• Experience in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models
• Experience writing code in Python, R, Scala, Java, C++ with documentation for reproducibility
• Experience handling terabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL, and working with GPUs to develop models
• Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations

Preferred Qualifications

  • PhD in a quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics)
  • Skills with programming languages such as Java or C/C++
  • Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, and determine cause and effect relations
  • Consulting experience with AI customers and use cases
  • Publications or presentations at Machine Learning, Deep Learning and Data Mining journals/conferences
  • Experience with AWS technologies like Redshift, S3, EC2, Data Pipeline, & EMR
  • Experience using ML libraries, such as scikit-learn, caret, mlr, or mllib
  • Combination of deep technical and business savvy skills to interface with all levels and disciplines within our customers' organizations
  • Track record of dealing with ambiguity, prioritizing needs, and delivering results in a dynamic environment
  • We are hiring Data Scientists for multiple experience levels. Location is open - our Data Scientists can be based out of any of our US office locations.


Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

For employees based in Colorado, this position starts at $125,000 per year. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a range of medical, financial, and/or other benefits, dependent on the position offered

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.

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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.

Tags: AWS Big Data C++ Computer Science Computer Vision Consulting Data Mining Data visualization Deep Learning DevOps EC2 Machine Learning Mathematics ML models MXNet NLP PhD Predictive modeling Python PyTorch R Redshift Research Scala Scikit-learn Security SparkML SQL Statistics TensorFlow

Perks/benefits: Career development Conferences Flex hours Salary bonus Signing bonus Startup environment Team events

Regions: Remote/Anywhere North America
Country: United States
Job stats:  3  0  0
Category: Data Science Jobs

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