招聘
As the Senior AI Scientist, you will work alongside industry experts developing and applying cutting edge ML & AI algorithms to optimize Best Buy customer experience. The systems you build will power customer experiences responsible for billions of dollars in revenues from home page, search, recommendations to checkout and post-purchase. You will work in a dynamic team tackling a variety of use cases including understanding search intent, intelligently optimizing the page layout, deciding what products to be shown in carousels, trading off between giving customers what they want vs allowing for serendipity, etc. You will work alongside a fast-paced team enabling ideas to often go into production in a matter of weeks.
This role is remote eligible, which means you would work virtually from home or another non-Best Buy location.
What you’ll do
- Design and implement large-scale Search, Rec Sys, Personalization and Adtech systems that power customer experiences across Best Buy surfaces.
- Derive complex features from large scale clickstream logs for model training data
- Develop & finetune retrieval/ranking models using supervised learning, deep learning, LLMs, and generative AI (e.g., Two Tower models, Sequence models, GNNs, etc.)
- Design custom evaluation metrics for measuring quality of ML and GenAI models.
- Collaborate with AI engineers, platform and product teams to deploy low latency models.
Basic qualifications
- Bachelor's degree in a highly quantitative field (Computer Science, Engineering, Physics, Math, Operations Research or related) or equivalent experience
- Strong machine learning and algorithmic background with a deep understanding of supervised and unsupervised learning methods, deep learning, LLMs.
- 4 years of experience building ML and/or AI driven products or other similar related functions (e.g. software engineering, data science, advanced analytics). Advanced degrees in relevant fields may be counted towards experience requirements.
- 2 years experience working on industrial-grade Search, Rec Sys, Personalization or Adtech.
- Strong skills in SQL and at least 1 programming language (e.g., Python, Julia)
Preferred qualifications
- Master's degree or Ph.D in a highly quantitative field (Computer Science, Engineering, Physics, Math, Operations Research or related)
- Experience building production grade ML models using one or more Deep Learning frameworks like Tensor Flow, Keras, Py Torch, etc.
- Cross-functional experience in deploying realtime low-latency ML products over GCP or AWS
What’s in it for you
We’re committed to helping you thrive at work and at home with benefits that support your total well‑being, including:
- Competitive pay
- Generous employee discount
- Physical and mental well‑being support
About us
As part of the Best Buy team, you’ll help us fulfill our purpose to enrich lives through technology. We bring that to life by humanizing and personalizing tech solutions for every stage of life — in stores, online, and in customers’ homes. Our culture is built on supporting our people and creating space for you to bring your full, authentic self to work. Tomorrow works here.™
Best Buy is an equal opportunity employer.
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关于Best Buy

Best Buy
PublicBest Buy Co., Inc. is an American multinational consumer electronics retailer headquartered in Richfield, Minnesota. Originally founded by Richard M.
10,001+
员工数
Richfield
总部位置
$7.8B
企业估值
评价
4.0
10条评价
工作生活平衡
3.2
薪酬
3.4
企业文化
4.1
职业发展
3.8
管理层
2.8
72%
推荐给朋友
优点
Great team environment and support
Good training and development programs
Flexible scheduling options
缺点
Work-life balance challenges and long hours
High pressure during sales events and peak times
Pay could be better
薪资范围
12,325个数据点
L2
L3
L4
L5
L6
M3
M4
M5
M6
Mid/L4
Senior/L5
L2 · Data Scientist L2
0份报告
$94,250
年薪总额
基本工资
$37,700
股票
$47,125
奖金
$9,425
$65,975
$122,525
面试经验
4次面试
难度
3.0
/ 5
时长
21-35周
录用率
50%
体验
正面 0%
中性 25%
负面 75%
面试流程
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-Person Interview
5
Offer
常见问题
Behavioral/STAR
Past Experience
Culture Fit
Customer Service Scenarios
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