Senior Data Scientist, AIGC HR Analytics Job at Amazon.com Services LLC, Seattle, WA

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  • Amazon.com Services LLC
  • Seattle, WA

Job Description

DESCRIPTION

Amazon Ads/IMDb/Grand Challenge (AIGC) HR Analytics (AHA) team is looking for a Senior Data Scientist who wants to work in a fast-paced, exciting, and growing organization.

We are actively looking to hire senior scientists to lead one or more of these problem spaces. Successful candidates will have a deep knowledge of Anomaly detection and Machine Learning methods, experience in applying these methods to large-scale business problems, the ability to map models into production-worthy code in Python or Java, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big research challenges. As a member of our team, you'll work on cutting-edge projects that directly impact AIGC employees.

The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and outstanding ability in balancing technical leadership with strong business judgment to make the right decisions about model and method choices. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. If you enjoy innovating, thinking big and want to contribute directly to the success of a growing team, you may be a prime candidate for this position.

Key job responsibilities
In this role you will:

• Analyze, model and interpret data for AIGC employees
• Build anomaly detection tools for people metrics to optimize org structure
• Data analysis, modeling, network flow prediction using Excel, Pivot tables, VBA, Tableau, SQL (Amazon Redshift), R, Python
• Predictive analysis using Machine Learning models at scale
• Create effective data analysis reports and communicate with stakeholders
• Innovate and simplify data analysis process to standardize and enable automation

About the team
Our team communicates who we are as an employer – what it’s like to be an Amazonian, why we love innovating on behalf of customers and why people should join us. We build trust with our partners, dive deep into our data, and love to learn and be curious as we deliver results. Our job is to bring that to life.

Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Inclusive Team Culture
Here at Amazon, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

BASIC QUALIFICATIONS

- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 6+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

Job Tags

Full time,

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