AmazonData Scientist, LM Planning, LM Science & Analytics Automation
Amazon is hiring a Data Scientist, LM Planning, LM Science & Analytics Automation in Bellevue, United States. It pays $136k-$184k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- On Level's scale, this data scientist role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Python, AWS and LLMs among its tools and skills.
- Level classes it as a senior role.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Senior Data Scientist developing mathematical, statistical, and LLM-based optimization models for last-mile delivery network topology and strategy.
Amazon Last Mile Strategic Planning is looking for Sr. Data Scientists, developing solutions to optimize our delivery network topology, strategically maximizing Customer Experience and minimizing cost to serve and increase speed.
You will partner with the Scientific community to help design optimization and strategy. You will also collaborate with technical teams developing automated tools for network flow and execution systems. You will work directly with business leadership and operational stakeholders to influence their strategy and gather inputs to solve problems.
To be successful in the role, you will need deep analytical skills and a strong scientific background. The role also requires excellent communication skills, translating technical contents to business friendly narrative. Ability to influence across business functions at different levels, including your own team.
You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with data, science, business and technical teams.
Key job responsibilities
-Design and develop mathematical, statistical and optimization models to optimize Delivery Network Topology design..
-Manage several, high impact projects simultaneously
-Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize Delivery Network Topology
-Communicate data-driven insights and recommendations to diverse stakeholders through technical and/or business papers
-Leverage LLMs to improve explainability of optimization and drive engagement from volume planning, demand planning stakeholders
-Define measurement frameworks for optimization solutions where no prior art exists and own the scientific framework for ‘Topology Plans’ multi-contact journey
-Choose the right methods (statistical, causal, ML, LLM, hybrid) for each problem and justify trade-offs. Drive excellence in evaluation: ground-truth construction with Quality auditors, human audits, precision/recall, drift, calibration, bias, safety, and cost
- Design driver-analysis and bridging methods explaining KPI movement (WoW, MoM, YoY, vs OP2) across dimensions for "why"
- Partner with teams in productionizing; Own AWS tech stack compliancy (Shepherd risk, App Security red-certification, Kale, Legal, Threat Models, for scientific assets)
- Mentor team members; provide promotion assessments; contribute hiring at DS II and DS III. Represent LM Planning in the broader Amazon Data Science community
- Produce design and technical documentation
A day in the life
Review current solutions, assumptions and question the status quo to find improvements.
Drive technical partners adopt improvements, to increase coding velocity, accuracy, quality of scientific solutions. Research for reusable tools/techniques and translate adopting to
About the team
Last Mile is the final mile of Amazon purchase. We- LM Strategic Planning ‘design and plan the Delivery Station Network’. LM network continues to grow multi-fold in North America, AMET, Emerging Market countries, delivering better customer experience and speed to customers. This growth will help Amazon gain most of distribution network share, in every country across the world. LM Strategic Planning-Science Analytics & Automation provides foundational solutions for network expansion roadmap that looks a 1-5 years horizon.
Basic 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
- 1+ years of guiding and coaching a group of researchers experience
- 1+ years of working with or evaluating AI systems experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
Preferred qualifications
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python, Perl, or another scripting language
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually
How we rate this
Data Scientist, LM Planning, LM Science & Analytics Automation at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● 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
Pay
- This job starts at
- $136k
- Typical data scientist job
- $168k
This posting starts 19% below the typical data scientist job. See data scientist jobs
Questions you could be asked
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where optimization was part of your work. What did you do?
- Tell me about a project where statistical modeling was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Walk me through how you've used Python in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Science, Optimization, Statistical Modeling, Machine learning, and Python. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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