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Senior Data Scientist - AWS Professional Services

Job ID: 1501502 | Amazon Web Services Canada, In


Excited by using massive amounts of to Machine Learning (ML) and Deep Learning (DL) models? Want to help the largest global enterprises derive business value through the adoption of Artificial Intelligence (AI)? You will be eager to learn from many different enterprise’s use cases of AWS ML and DL. You are thrilled to be a 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 and against a wide spectrum of problems. Our Professional Services organization works together with our AWS customers to address their business needs using AI.

AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you have experience with AI, including building ML or DL models, we’d like to have you join our team. You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers.

You enjoy diving deep into , doing analysis, discovering root causes, and designing long-term solutions. You like to have fun, love to learn, and want to innovate in the world of AI.

You will:
· 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 , exploring , building & validating predictive models, and deploying completed models to deliver business impact to the organization.
· Use Deep Learning frameworks like MXNet, Caffe 2, Tensorflow, Theano, CNTK, and Keras 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 consultants to analyze, extract, normalize, and label relevant .
· Work with our Professional Services DevOps consultants to help our customers operationalize models after they are .
· Assist customers with identifying model drift and retraining models.
· Research and novel ML and DL approaches, including using FPGA.
· Be able to write production level code, which is well-written and explainable
· Have experience using ML libraries, such as scikit-learn, caret, mlr, mllib
· Have experience working with GPUs to models
· Have experience handling terabyte size datasets
· Be able to track record of diving into data to discover hidden patterns
· Have familiarity with using data visualization tools
· Have 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
This role is for Toronto/Vancouver/Calgary/Montreal.

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 value on work-live 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 and enable them to take on more complex tasks in the future.


· A Bachelor or Masters Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent experience
· 10+ years of industry experience in predictive modeling, science and analysis
· Previous experience in a ML or scientist role and a track record of building ML or DL models
· Experience using and/or R
· Knowledge of SparkML


· PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
· 12+ years of industry experience in predictive modeling and analysis
· Good skills with programming languages, such as or C/C++
· Ability to experimental and analytic plans for 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 Mining journals/conferences
· Experience with AWS technologies like Redshift, S3, EC2, 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 providing accommodations at all stages through recruitment and employment in accordance with applicable human rights and accommodation legislation. If contacted for an employment opportunity, advise Human Resources if you require accommodation, including in order to apply for a position.