Senior Data Scientist

Job Overview

DESCRIPTION

Are you passionate to use your skills in Machine Learning (ML) and Deep Learning (DL) models to drive innovation? Do you want to help build innovative products for the Enterprise using Artificial Intelligence (AI)? We are looking for a Sr. Data Scientist with excellent analytical abilities, outstanding business acumen and judgment, intense curiosity, strong technical skills, and superior written and verbal communication skills to join the AWS Systems Manager team.

AWS Systems Manager is one of the fastest growing services in AWS, managing millions of EC2 instances and other resources every day. AWS Systems Manager is a set of services for managing resources safely and securely at scale in AWS. Systems Manager simplifies resource and application management, shortens time to detect and resolve operational problems, provides a unified user interface to view operational data from multiple AWS services, and allows users to automate operational tasks. Managing mission-critical infrastructure in the cloud in a reliable way is absolutely important to AWS customers and we are a core part of that story. IT administrators and DevOps engineers rely on us to help them manage their infrastructure, track the configuration and compliance of their AWS resources.

A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI. As a Data Scientist, your role will be to leverage the past data to make future predictions. You must deal with incomplete, messy, unorganized data, not immediately usable without some degree of cleaning and prepping. You will generate predictive insights and new product innovations by applying advanced analytical tools and algorithms utilizing advanced statistical packages, SQL, and open source tools like Python and Perl.

About Us

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. 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 remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many 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 believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

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. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

BASIC QUALIFICATIONS

· A Bachelor or Master’s Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent experience
· 5+ years of industry experience in predictive modeling, data science and analysis
· Previous experience in a ML or data scientist role and a track record of building ML or DL models
· Experience using Python and/or R
· Knowledge of SparkML
· Able to write production level code, which is well-written and explainable
· Experience handling terabyte size datasets
· Track record of diving into data to discover hidden patterns
· Familiarity with using data visualization tools
· Knowledge and experience of writing and tuning SQL
· Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
· Experience giving data presentations
· Extended travel to customer locations may be required to deliver professional services, as needed
· Strong written and verbal communication skills

PREFERRED QUALIFICATIONS

· PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
· 8+ years of industry experience in predictive modeling and analysis
· Good 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, ability to accurately determine cause and effect relations
· Consulting experience and track record of helping customers with their AI needs
· Publications or presentation in recognized Machine Learning, Deep Learning and Data Mining journals/conferences
· Experience with AWS technologies like Redshift, S3, EC2, Data Pipeline, & EMR
· Combination of deep technical skills and business savvy enough to interface with all levels and disciplines within our customer’s organization
· Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

Amazon is committed to a diverse and inclusive workplace.

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