Senior Customer Delivery Architect - Data Science

San Francisco, California, USA

Full Time
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Posted 1 week ago

Location is flexible anywhere in the US.
At Amazon Web Services (AWS), we are helping large enterprises build Machine Learning (ML) models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems.

AWS Professional Services team members leverage their deep knowledge of Artificial Intelligence and Machine Learning (AI/ML) and AWS technologies in collaboration with our sales and partner teams to propose, architect, and implement transformational solutions for customers, and helping them drive business outcomes. Helping make customer success a reality using AI/ML as an enabler and seeing the impact in real-time drives our teams to explore new frontiers in leveraging AWS for our customers.

The AI/ML Customer Delivery Architect (CDA) is a growth role within the Professional Services. The CDAs are responsible for partnering with a Professional Services’ sales team to dive deep into a customer’s business outcomes, to collaboratively propose technical approaches during sales pursuits, and pre-qualify a particular set of outcomes that would result from a formal data science (AI/ML) Professional Services engagement.
They have the unique ability to put together cutting-edge solutions that bring together data using a combination of deep technical knowledge, sales/business acumen, and strong interpersonal skills. Thereafter, the CDA remains meaningfully engaged on a part-time basis with that customer, Amazon team, and project/ program to provide oversight resulting in high-value, predictable, and successful delivery. A successful candidate will enjoy diving deep into data, doing analysis, discovering root causes, and proposing long-term solutions using AWS AI/ML and other services.

This is a hybrid role requiring exceptional sales support and delivery skills. The person in this role will come with a unique and broad data science expertise, strong interpersonal skills, experience in selling and hands-on building, coupled with cross-industry business acumen, including a heavy dose of passion for continued knowledge acquisition and growth, obsession for customers and their success using AWS to align with the desired business outcomes.


ROLE AND RESPONSIBILITIES
· In partnership with the ProServe sales and AWS account teams, educate customers on the value proposition of AWS and participate in deep architectural discussions and design exercises to create world-class AI/ML solutions built on AWS while ensuring such solutions are designed for successful deployment in the cloud to drive business outcomes
· Assist the AWS account teams and customers by conceptualizing and delivering end-to-end AI/ML proof-of-concepts and pilots, including understanding the business needs, aggregating and processing data, exploring data, building & validating predictive models, and deploying models with concept-drift monitoring and retraining to deliver business impact to the organization
· Research and implement novel AI/ML approaches, including hardware optimizations on platforms such as AWS Inferentia
· Work with other Professional Services teams to analyze, extract, normalize, and label relevant data, and work with the Data/ML engineers as needed to prototype customers’ models during the pre/post sales cycle
· Author or otherwise contribute to AWS internal and customer-facing publications such as whitepapers, blogs and proof of concepts
· Build deep relationships with senior technical resources within customers to enable them to be cloud advocates
· Capture and share best-practice knowledge, sales and delivery content amongst the AWS Professional Services community
This is a customer-facing role and you will be required to travel to client locations and deliver professional services as needed.


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
· 8+ years of industry experience working with external or internal customers in selling and developing predictive modeling, data science, and analysis including:
· Experience writing code in Python, R, Scala, Java, C++ with documentation for reproducibility
· Experience with current Machine Learning and Data Analytics tools and libraries
· Experience in handling terabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, SQL programming, and working with GPUs to develop models

Preferred Qualifications

·
· Master’s degree or PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
· Publications or presentations in recognized ML journals or conferences
· Strong organizational skills with an ability to manage numerous demands from internal / external stakeholders and customers
· Experience in scoping out and/or delivering large enterprise scale Machine Learning projects and applications
· Deep domain expertise in Machine Learning and/or Industry domains
· Ability to collaborate with global/enterprise account sales and delivery teams to drive adoption of AI/ML Solutions into top accounts
· Familiarity with AWS AI services (e.g., Amazon Personalize), ML platforms (Amazon SageMaker), and open-source frameworks (e.g., MXNet, TensorFlow, PyTorch, SparkML, scikit-learn) to help our customers build AI/ML models

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.

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



Job tags: AI AWS Data Analytics Java Machine Learning ML MXNet Python PyTorch R Research Scala Scikit-Learn SparkML SQL TensorFlow Travel