Applied Scientist II, IN SPS Tech
Amazon is hiring an Applied Scientist II, IN SPS Tech in Bengaluru, India. Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
- The posting mentions Python, machine learning and operations research among its tools and skills.
- Level classes it as a mid-level role.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Design, build, and optimize machine learning models and algorithms to enhance marketplace selection quality and revenue.
The IN Seller Partner Services Tech organization is responsible for building delightful seller experiences with the vision of being the technology foundation that makes Amazon the #1 choice for sellers of all types and price-sensitive customers in India and emerging markets—transforming how a billion people buy and sell, thereby transforming lives. By making its sellers successful, Amazon can attract and retain sellers on the platform, which in turn offers its customers the best selection, convenience, pricing and experience resulting in multi-billion-dollar business. This organization enables sellers of all stripes across a multitude of business lines existing or new such as Q-Commerce, Pharmacy and Out of country selling.
We are looking for a motivated and innovative Applied Scientist with strong analytical skills and practical experience to join our science team. As a key member of our science team, you will provide expertise that helps accelerate the business and make it profitable. You will research, design and improve on the models that will directly impact Amazon’s Selection quality and maximize fee revenue. You will be working in a highly collaborative environment partnering with various science, product management, engineering, operations, finance, business intelligence and analytics teams. You will need to understand the business requirements and translate them into complex analytical outputs. You will design tests to explain performance of the models from impact on customer and cost perspective. You will create ML models to capture features impacting performance. You should be comfortable building prototypes, testing and improving them given the feedback from the real time data. You should be able to present your model and findings to a various range of stakeholders.
Looking for candidate with expertise in the areas of machine learning, operations research, and statistics. With expertise in applying theoretical models in an applied environment relying heavily on the latest advances in machine learning, optimization, stochastic modeling, and engineering. The candidate will be expected to work on numerous aspects, such as feature engineering, modeling, probabilistic modeling, hyper-parameter tuning, scalable inference methods and latent variable models. Challenges will involve dealing with very large data sets and requirements on throughput.
Key job responsibilities
- Design, implement, test, deploy, and maintain innovative science solutions to accelerate our business.
- Create experiments and prototype implementations of new learning algorithms and prediction techniques
- Collaborate with scientists, engineers, product managers, and stakeholders to design and implement software solutions for science problems
- Use best practices to ensure a high standard of quality for all of the team deliverables
Basic qualifications
- Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 3+ years of building machine learning models or developing algorithms for business application experience
- 3+ years of solving business problems through machine learning, data mining and statistical algorithms experience
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in professional software development
- Experience implementing algorithms using toolkits and self-developed code
Preferred qualifications
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 5+ years of building machine learning models or developing algorithms for business application experience
- Knowledge of architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members
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.
How we rate this
Applied Scientist II, IN SPS Tech at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in applied scientist jobs at this level
Pay
- Typical applied scientist job
- $169k
This posting doesn't list pay. Use the typical applied scientist figure when pay comes up. See applied scientist jobs
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where operations research was part of your work. What did you do?
- Tell me about a project where statistics was part of your work. What did you do?
- Tell me about a project where feature engineering was part of your work. What did you do?
- Tell me about a project where probabilistic modeling was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Machine learning, Operations Research, Statistics, Feature Engineering, and Probabilistic Modeling. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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