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Jr. Applied Scientist - Job Opportunity at Amazon.com Services LLC

Santa Cruz, United States
Part-time
Entry-level
Posted: January 25, 2025
On-site
USD 16.83-75.63 per hour

Benefits

Flexible work schedule for students
1:1 mentorship with Amazon Applied Science experts
Potential full-time conversion opportunity
Medical and financial benefits package
Career development support

Key Responsibilities

Analyze large-scale data sets and develop machine learning solutions
Collaborate with product managers on technical implementations
Drive scientific vision for products alongside senior scientists
Build metrics and performance analysis frameworks
Contribute to real-world machine learning applications

Requirements

Education

Currently enrolled in Master's degree program in Computer Science, Statistics or related STEM discipline

Experience

Previous technical internship(s)

Required Skills

Machine learning Data analysis Problem-solving Technical communication Ability to handle ambiguous problems Abstract thinking
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Sauge AI Market Intelligence

Industry Trends

Growing demand for applied AI/ML specialists in tech companies as AI adoption accelerates Increasing emphasis on practical machine learning experience alongside academic credentials Rising importance of mentorship programs in technical talent development

Salary Evaluation

The wide salary range ($35,000-$157,000 annualized) reflects both part-time/full-time flexibility and regional market variations, with experienced ML specialists typically commanding upper range compensation

Role Significance

Typically part of a 5-8 person applied science team, working closely with 1-2 senior scientists and product teams
Entry-level position with significant growth potential, structured as a pipeline for future senior technical roles

Key Projects

Machine learning model development for Amazon's core services Data pipeline optimization and analysis Customer experience enhancement through ML applications Product performance metrics development

Success Factors

Strong foundation in theoretical ML concepts combined with practical implementation skills Ability to balance academic commitments with professional responsibilities Excellent communication skills to bridge technical and business contexts Proactive learning mindset and ability to adapt to rapid technological changes

Market Demand

Very high demand with sustained growth projected. Applied ML roles are among the fastest-growing technical positions in the industry.

Important Skills

Critical Skills

Machine Learning Fundamentals: Essential for core job functions and future growth Data Analysis: Key for extracting meaningful insights from large datasets Programming Skills: Necessary for implementing ML solutions Communication: Critical for collaborating with cross-functional teams

Beneficial Skills

Cloud Computing Knowledge: Valuable for working with Amazon's infrastructure Distributed Systems Understanding: Helpful for large-scale implementations Product Sense: Important for aligning technical solutions with business needs

Unique Aspects

Year-round part-time structure allows for concurrent academic and professional development
Direct mentorship from industry leaders in applied science
Exposure to large-scale, real-world ML applications
Clear path to full-time conversion

Career Growth

2-3 years in role with potential for accelerated advancement based on performance and degree completion

Potential Next Roles

Applied Scientist Senior Applied Scientist Machine Learning Engineer Research Scientist

Company Overview

Amazon.com Services LLC

Amazon leads in applying ML/AI at scale across e-commerce, cloud computing, and various technological domains

Top-tier technology company with significant investments in AI/ML research and applications
Santa Cruz location represents strategic expansion of Amazon's technical operations beyond traditional tech hubs
Fast-paced, innovation-focused environment with emphasis on ownership and customer obsession
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  • Industry trends and market dynamics
  • Salary estimates and market demand analysis
  • Role significance and career growth potential
  • Critical success factors and key skills
  • Unique aspects of each position

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