Applied Scientist Ii, Alexa International
7 days ago
Masters in Computer Science, Machine Learning, Operations Research, Statistics or a related quantitative field
- 3+ years of hands-on experience in predictive modeling and analysis
- 2+ years of hands-on experience in Python, Perl, Scala, Java, C#, C++ or other similar languages
- 1+ years of professional experience in software development
- Ability to convey mathematical results to non-science stakeholders Strength in clarifying and formalizing complex problems
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts
Job summary
Come join the Alexa International team and help us invent Alexa's future across International marketplace.
We are hiring experienced scientists with entrepreneurial spirit to join us in this highly visible opportunity. You will have influence on our overall strategy by helping to define ML solutions for our product features and capabilities and spearhead the best practices that enable smart solutions. If you have an entrepreneurial spirit, know how to deliver, are technical and innovative, and relish the opportunity to delight customers, we want to talk to you.
Key job responsibilities
- Researching, designing, implementing, testing, deploying, and maintain innovative models and machine learning solutions to make our solutions more smarter and customize the customer experience.
- Creating experiments and prototype implementations of new learning algorithms and prediction techniques
- Produce peer-reviewed research reports reaching the same level of correctness, scholarliness, usefulness, completeness, depth and rigor and/or originality as a respected peer-reviewed external publication. Where appropriate, you submit to internal and external publication venues
- Participate in team design, scoping and prioritization discussions
- Use machine learning best practices to ensure a high standard of quality for all of the team deliverables
A day in the life
- Significant peer reviewed scientific contributions in relevant field
- Strong fundamentals in problem solving, algorithm design and complexity analysis
- Strong personal interest in learning, researching, and creating new technologies with high commercial impact
- Experience with defining organizational research and development practices in an industry setting
- Proven track in leading, mentoring and growing teams of scientists
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