Job summary
Job post source
This job is from a recruiting firm hiring for a separate company, Amazon, as the description focuses on Amazon's role and does not indicate direct hiring by Jobright.ai.
Job overview
The Early Career Applied Scientist role involves building causal and machine learning models to support business decisions and contributing to scalable data and modeling infrastructure at Amazon.
Responsibilities and impact
The candidate will build business application models, program in Python or similar languages, use distributed computing frameworks like Spark, and apply knowledge in algorithms, numerical optimization, high-performance computing, and Bayesian statistics.
Experience and skills
Required qualifications include a PhD or Master's in CS, CE, ML or related fields, experience in model building, Python programming, Spark, and statistical methods; preferred qualifications include professional software development, generative AI, LLMs, large-scale modeling, causal inference, and publications or patents.
Company information
Amazon is a tech firm specializing in e-commerce, cloud computing, digital streaming, and AI.
Company overview
Jobright.ai is a technology company focused on leveraging artificial intelligence to streamline and enhance the job search and recruitment process for both candidates and employers. The company generates revenue primarily through subscription-based services and partnerships with organizations seeking to optimize hiring, offering tools such as AI-powered resume analysis, job matching, and interview preparation. Founded to address inefficiencies in traditional recruitment, Jobright.ai has positioned itself as an innovator in the HR tech space, emphasizing automation and data-driven insights. Notable milestones include the launch of its proprietary AI algorithms and collaborations with major job boards and corporate clients. Candidates should be aware of Jobright.ai’s commitment to ethical AI practices and its rapidly evolving product suite.
How to land this job
Tailor your resume to emphasize your experience building machine learning and causal models for business applications, highlighting any projects or coursework involving Python and distributed computing frameworks like Spark.
Highlight your technical skills in algorithms, data structures, numerical optimization, high-performance computing, and Bayesian statistics, as these are key requirements for the role.
Apply through multiple channels including Jobright.ai's corporate career page, LinkedIn job postings, and other reputable job boards to maximize your chances of being noticed.
Connect with early career scientists or machine learning team members at Jobright.ai on LinkedIn; start conversations by referencing recent AI projects they have worked on or asking about the team’s approach to causal inference and modeling pipelines.
Optimize your resume for ATS by incorporating exact keywords from the job description such as 'causal machine learning,' 'Python,' 'Spark,' 'numerical optimization,' and 'Bayesian statistics' to ensure your resume passes automated screenings.
Leverage Jennie Johnson's Power Apply feature to automate tailoring your resume, identify the best application portals, and find relevant LinkedIn contacts, allowing you to focus more on interview preparation and skill enhancement.
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