Jr. Applied Scientist

shefsolutionsllc; Austin (TX); On-site; USD 27,552 - 41,328; Part time

Benefits offered by this job

Flexible work schedules

Mentorship from experienced professionals

Job summary

A leading tech company in Austin, TX is offering a Jr. Applied Scientist internship aimed at Master's students. This role emphasizes hands-on applied science and machine learning experience, with one-on-one mentoring from experienced professionals. Candidates will conduct meaningful projects that directly impact customer experience and have opportunities for full-time employment post-graduation. Flexible work schedules are available to accommodate schooling.

Qualifications

• Previous technical internship(s) required.
• Ability to articulate technical challenges effectively.
• Adept at handling ambiguous or undefined problems.

Responsibilities

• Drive the scientific vision for Amazon's products.
• Collaborate with teams building machine learning solutions.
• Analyze large datasets to solve real-world problems.
• Use customer insights to enhance customer experience.

Skills

Technical communication

Problem solving

Machine Learning

Statistical analysis

Education

Currently enrolled in a Master's degree program

Job description

The Jr. Applied Scientist role is a unique employment opportunity for students seeking to gain on‑the‑job applied science and machine learning experience and receive excellent mentoring while completing their education. Jr. Applied Scientists are immersed in an Amazon team and work on exciting, meaningful projects that impact real Amazon customers. Paired 1:1 with an Amazon Applied Science Mentor, Jr. Applied Scientists receive guidance and support in all aspects of their role: skill development, career advisement, project collaboration, and more! Upon successful completion of your degree and success in the Jr. Applied Scientist role, the opportunity for full‑time employment will be available at the Amazon corporate site in Austin, TX. The Jr. Applied Scientist role is part of the Jr. Developer Program, a unique internship program in several respects:

• Currently enrolled in an accredited college or university Master’s degree program.
• Majoring in Computer Science, Statistics or a related STEM discipline.
• Graduation date falls in May/June 2027 and beyond.
• Ability to work year‑round: part‑time during the school year and full‑time during the summer.
• Living within commutable distance to Austin, TX and able to work in‑person for all hours.

We offer work year‑round, part‑time (16 hrs/week) while in school and full‑time (40 hrs/week) during summer. Working schedules are flexible and can be re‑arranged each quarter to accommodate class schedules. We offer excellent mentoring. Our full‑time applied scientists, data scientists, business intelligence engineers, and software development engineers are willing and able to mentor exceptional student applied scientists, data scientists, SDEs, and BIEs. Jr. Applied Scientists are given responsibilities and roles that prepare them to enter the workforce after graduation with “real world” applied science and machine learning experience. Jrs. who participate in the Jr. Developer Program routinely acknowledge the valuable learning experience created by the uniform excellence of their teams, mentoring offered by experienced Amazonians, and the challenge of being a principal contributor to science and software products.

Key job responsibilities

• Amazon applied scientists are specialists with the knowledge to help drive the scientific vision for our products. They are aware of the state‑of‑the‑art in their respective field of expertise and are constantly focused on advancing that state‑of‑the‑art for improving Amazon’s products and services.
• As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with distributed systems of data and providing technical partnership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi‑supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation.
• This individual will analyze large amounts of data, discover and solve real world problems and build metrics and business cases around key performance of this program.
• The ideal candidate will use a customer‑backwards approach in deriving insights and identifying actions we can take to improve the customer experience and conversion for the program.

Qualifications

• Previous technical internship(s).
• Effectively articulate technical challenges and solutions.
• Adept at handling ambiguous or undefined problems as well as ability to think abstractly.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.