Applied Science Manager, AWS Insights & Optimizations

Key Skills

Java Programming, Python Programming, SQL, Bayesian networks

Job Description

Job summary

Amazon Web Services is looking for experienced Applied Science Managers to join AWS Insights and Optimizations, lead a team of Data and Applied Scientists in delivering ground-breaking solutions for customers utilizing state of the art and state of the practice methods in ML, AI and Optimization. This position will support customer facing services such as Cost Anomaly Detection, Workload Recommender Systems, Forecasting, Compute Optimization. On this team, you will help guide and lead team of scientists who invent and implement innovative solutions for never-before-solved problems. This is not solely a management role, you will be directly contributing to the research and development while you lead. If you have passion for applied data scientist and experience with managing scientists, this will be an exciting opportunity.

The ideal candidate will care deeply to develop their team while inventing on behalf of customers and have a strong interest in Machine Learning. We are a team of Data and Applied Scientists what is engaged with engineering teams throughout the entire product lifecycle to deliver end-to-end solutions. And, of course, the candidate MUST be willing to learn new technologies.

A commitment to lead the team work and communication skills are important in this role. Creating reliable, scalable, and high-performance ML / AI solutions requires exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, some background in Mathematics and Statistics, and practical experience building large-scale distributed systems.

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.

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.

Key job responsibilities

• Lead scientists and engineers on the team and oversee research and development projects at various stages ranging from initial exploration to deployment into production systems.
• Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.
• Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.
• Report results in a scientifically rigorous way.
• Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.

BASIC QUALIFICATIONS

• Ms in Computer Science, Engineering, Mathematics or a related quantitative field
• 3+ years’ experience in managing, mentoring and leading a technical development team including applied scientists and software engineers.
• 5+ years of hands-on experience in predictive modeling and analysis
• 2+ years of algorithm development experience
• Hands-on architectural or system design experience.
• Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams.

PREFERRED QUALIFICATIONS

• Proven track record of managing science teams, hiring and developing science talent
• 10+ years of relevant experience in industry and/or academia.
• Extensive experience applying theoretical models in an applied environment.
• Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametric methods.