Snowflake is growing fast and they’re scaling their team to help enable and accelerate their growth. They’re passionate about their people, their customers, their values and their culture! They’re also looking for people with a growth mindset and the pragmatic insight to solve for today while building for the future. And as a Snowflake employee, you will be accountable for supporting and enabling diversity and belonging.
Snowflake started with a clear vision: make modern data warehousing effective, affordable, and accessible to all data users. Because traditional on-premises and cloud solutions struggle with this, Snowflake developed an innovative product with a new built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions.
In addition, Snowflake’s culture was built on the following values that are even more important to us today:
Put Customers First. We only succeed when our customers succeed
Integrity Always. Be open, honest, and respectful
Think Big. Be ambitious and have big goals
Be Excellent. Quality and excellence count in everything we do
Get It Done. Results matter!
Make Each Other the Best
Embrace each others Differences
In this role you will work closely with Product Managers, Analysts, and Engineers to help build data products that inform customers how to optimize their use of Snowflake. You will uncover insights about how customers use Snowflake. And you will work on research projects to help drive our long-run Product strategy.
As a Data Scientist, You Will
- Sleuth through large amounts of data to uncover feature-usage patterns, potential performance enhancements, and areas to improve user experience.
- Build data products that help inform their customers how to optimize their use of Snowflake.
- Identify and build solutions for operational use cases—e.g., system monitoring and alerting, outlier detection, etc.
- Help design and execute experiments and A/B tests.
- Use data to make recommendations on how to improve their self-service experience.
- Think creatively to find optimal solutions to their complex, typically unstructured problems.
Their Ideal Candidate Will Have
- 5+ years of experience working as a Data Scientist.
- 3+ years of experience working with truly large-scale data.
- Advanced SQL skills.
- Strong written and verbal communication skills.
- Expert-level abilities building and deploying unsupervised, semi-supervised, and supervised models on large-scale data (in that order of importance).
- A fluidity with tools commonly used for data analysis such as Python (numpy, pandas, and scikit learn), R, and Spark (MLlib).
- Experience with time-series forecasting.
- Experience building and deploying production-grade models in a real-time setting.
- Experience with a compiled programming language, preferably something that runs on the JVM.
- Experience with MPP databases, such as Snowflake, Redshift, BigQuery, Vertica, etc.
- Familiarity with data visualization tools/frameworks as well as notebooks.
- A degree of comfort at the command line. That means a thorough understanding of basic file-system commands, as well as the ability to ssh into remote machines and troubleshoot without a GUI, grep through logs, and deploy scripts and applications.
- Familiarity with Git and/or SVN.
- The ability to thrive in a dynamic environment. That means being flexible and willing to jump in and do whatever it takes to be successful.
Please show them what you’ve built by including a link to your Github profile.
Snowflake is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1