一亩三分地

【Jerry.ai 内推】Data Team 扩招中，new grad 友好！

10388

查看帖子分类信息

Data Team大量扩招，目前有很多hc， new grad友好。SDE Team也有新的HC，欢迎同学们投简历~

关于我们：

北美唯一的人工智能金融产品选购平台，获得上亿元级别融资
产品自上线以来，季度营收指数增长
一个充满激情的工作氛围
一种开放透明的沟通文化
一群技术背景很强的同事（同事来自于：阿里, 亚马逊，微软，英伟达，华为等）

Jerry.ai 是一家具有强大技术背景的北美跨国高科技创新公司，目前在加拿大多伦多,美国硅谷以及纽约州均设有分部, 并在国内有一支全职开发团队。公司由美国名校博士联合创立，三位联合创始人具有丰富的硅谷连续创业经验，旗下产品利用大数据和人工智能技术与美国金融机构和保险公司进行数据对接与合作，从而为用户打造最快捷便利的人工智能金融和保险产品选购平台。自从我们的产品发布以来，在过去 15 个月内得到了迅速的增长（每月增长 30%以上）。

公司现有 100+ 名员工，技术团队背景非常多元化，团队成员均具有强大的技术背景和丰富的工作经验，大部分成员曾就职于知名科技企业，比如：微软，亚马逊，阿里巴巴，英伟达，华为，快手。近来，公司完成了上亿元级别融资，我们正在致力于新一轮的团队扩建。我们希望寻找具有丰富经验，喜爱技术挑的人才加入我们的队伍

1.Data Analyst
Responsibilities:

Owner of the core company data pipeline, responsible for scaling up data processing flow to meet the rapid data growth
Consistently evolve data model & data schema based on business and engineering needs
Implement systems tracking data quality and consistency
SQL and MapReduce job tuning to improve data processing performance

Requirements:

B.S. degree in a related discipline.
1+ years of data analysis experience.
Proficient in SQL, especially with Postgres dialect.
Expertise in Python for developing and maintaining data pipeline code.
Experience with BI software (preferably Metabase or Tableau).
Experience with Hadoop (or similar) Ecosystem.
Comfortable working directly with data analytics to bridge business requirements with data engineering

2. Data Engineer
Responsibilities:

Managing our ETL pipelines
Business Intelligence:

Determine and procure tooling/platform
BI request workflow (business need -> report)
Version control of queries/dashboards
Determine and maintain correctness of data (data quality)

Machine Learning:

Select and deploy a platform for ML
Determine architecture for Jerry interacting with and utilizing the ML output in business logic (i.e. APIs, etc)
Take MVP model built by data scientist and ‘productize’ it (i.e. implement/integrate it in production system)
Reports on performance of deployed ML models

Requirements:

Proficient in SQL, especially with Postgres dialect.
1+ years of data engineering experience.
Expertise in at least one programming language for implementing ML models and corresponding client APIs. Familiarity with NodeJS (our product dev language) is a plus.
Experience in packaging and deploying ML code in production environments. Experience with Docker required. Experience with Kubernetes is a plus.
Experience with BI software (preferably Metabase, Qlikview or Tableau).
Experience with deploying and maintaining data infrastructure in the cloud (experience with AWS Lambda -> AWS Kinesis -> AWS Redshift -> Metabase BI & AWS RDS preferred)
Comfortable working directly with data analytics to bridge business requirements with data engineering

3. Data Scientists:
Responsibilities

Identify valuable data sources and automate collection processes
Undertake to preprocess of structured and unstructured data
Analyze large amounts of information to discover trends and patterns
Build predictive models and machine-learning algorithms
Combine models through ensemble modeling
Present information using data visualization techniques
Propose solutions and strategies to business challenges

Requirements

Extensive experience with SQL
B.S. or M.S. in a quantitative field required. Ph.D. in similar fields a plus.
1-3 years experience with Statistical/Machine Learning, NLP, Deep Learning
Strong programming skills. Able to write algorithms needed for modeling and prediction that deals with advanced data structures.
Follow Data Science literature and advancements. The most successful candidates possess the ability to apply cutting edge advancements in Data Science methodologies to relevant business problems.

3. Software Engineer (all levels)
Requirements

本科及以上学历，计算机，软件工程相关专业，具备扎实的软件开发基础知识（数据结构，算法等等）
精通现代 javascript (ES6+: Classes, modules, arrow functions, async/await, destructuring, etc.)
精通Web 前端框架，如 ReactJs, Vue.js 等
了解服务器端渲染技术，以及 React Native 移动端开发
了解 javascript 的最佳实践和一些常用的设计模式，具备编写高效简洁的 javascript 代码
会编写和维护规范的测试集，有维护和管理大型代码 repo 的相关经验并且知道如何维护 repo 对代码的性能和* 可扩展性有深刻的理解
乐于编写高质量的代码和测试集，并维护全面的代码覆盖测试
具备良好的沟通能力

加分项目：