We are seeking a talented and analytical Data Scientist to join our team and drive data-driven insights and solutions. In this role, you will be responsible for performing exploratory data analysis, developing and deploying predictive models, and leveraging advanced analytics techniques to uncover valuable insights and support data-driven decision-making across the organization.
Key job responsibilities:
- Collaborate with our applied and data scientists to build robust and scalable Generative AI solutions for business problems.
- Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs.
- Work hands on to build scalable cloud environment for our customers to label data, build, train, tune and deploy their models.
- Interact with customers directly to understand the business problem, help and aid them in implementation of their ML ecosystem.
- Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes.
- Work closely with partner teams to drive model implementations and new algorithms.
About the team:
Amazon Web Services (AWS) provides a scalable cloud computing platform to companies globally. AWS Global Services (GS), formed in 2022, delivers customer success throughout the cloud adoption lifecycle. Our 25K+ employees and integrated offerings enable us to combine technology and human expertise to maximize and accelerate customer outcomes.
GS is comprised of four primary business units: 1) Global Services Security (GSS) provides security guidance and offerings, 2) Training & Certification (T&C) offers cloud skills training and certification, 3) Professional Services (ProServe) provides consulting and hands-on-keyboard services, and 4) Support and AWS Managed Services (Support) delivers 24/7 technical support and managed services.
Together, these teams continuously improve our systems and processes to enable better results for both customers and employees, with the GS Strategy & Operations (GSS) teams supporting each. GSSO enables integrated business support, product management, planning, and deal strategy for GS. GSSO understands customer experiences and inspires bold ideas to deliver the best experiences and solutions to our customers. We embrace scientific thinking, pursue continuous improvement, and develop talent to provide world-class support across GS.
Minimum Qualifications:
- 2+ years of data scientist experience.
- 3+ years of data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab, etc.) experience.
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
- Experience applying theoretical models in an applied environment.
- Experience in Python, Perl, or another scripting language.
- Experience in a ML or data scientist role with a large technology company.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit this link .
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit this link . This position will remain posted until filled. Applicants should apply via our internal or external career site.
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