Principal Data Scientist, Snowflake

Product

$209-326.6k

Plus bonus and equity plan

SQL

Python

Redshift

NumPy

Pandas

Scikit-Learn

Snowflake

BigQuery

Vertica

Expert level

San Francisco Bay Area

3-5 days a week in office (Menlo Park, CA)

AI Data Cloud for data sharing and app building

Open for applications

AI Data Cloud for data sharing and app building

1001+ employees

B2BArtificial IntelligenceData storageEnterpriseAnalyticsMachine LearningSaaSData AnalysisCloud ComputingData Sharing

Open for applications

$209-326.6k

Plus bonus and equity plan

SQL

Python

Redshift

NumPy

Pandas

Scikit-Learn

Snowflake

BigQuery

Vertica

Expert level

San Francisco Bay Area

3-5 days a week in office (Menlo Park, CA)

1001+ employees

B2BArtificial IntelligenceData storageEnterpriseAnalyticsMachine LearningSaaSData AnalysisCloud ComputingData Sharing

Company mission

On a mission to mobilize the world's data.

Job

Company

Role

Who you are

MS/Ph.D. in quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS)
12+ years of relevant data science or related experience
Expert-level experience working with SQL & Python including scikit-learn, numpy, and pandas
Expert in working with large-scale machine generated data (e.g., logs, application telemetry, or customer usage data)
High fluency with MPP databases, such as Snowflake, Redshift, BigQuery, Vertica, etc
Expert data-driven storytelling skills to convey insights to business leaders and technical stakeholders and influence decisions
The ability to thrive in a dynamic environment, being flexible and willing to jump in and do whatever it takes to contribute to the success of your area

What the job involves

The Product Data Science team is looking for a Full-stack Principal Data Scientist to come aboard and be part of Snowflake’s most critical initiatives
In this role, you will work closely with our Product and Engineering teams on everything from core operations, to innovative AI/ML tools, to our fastest-growing new and experimental features
You will work on long-running analytical initiatives yielding substantial product enhancements
This is a strategic, high-impact role that will help shape the future of Snowflake products and services
Be a proactive partner to Product Management and Engineering to shape feature roadmaps and help design metrics and analytical workflows to evaluate their success and effectiveness
Architect efficient data models and high quality production pipelines and partner with Engineering for all necessary telemetry
Build scalable and extensible analytics/ML/causal inference frameworks to uncover feature usage patterns, subtle issues with the system, potential performance enhancements, and areas to improve customer experience
Be an early adopter/pro user of Snowflake features and provide feedback on design parameters
Evaluate the right surface (Snowflake Notebook/Worksheet/Snowsight Dashboards/Streamlit Apps) to disseminate your insights for maximal impact
Influence decisions and drive initiatives with the Product Management and Engineering teams to drive better outcomes for our customers
Answer questions from the executive team for reporting to the board and contribute to industry reports and similar publications
Think creatively and be scrappy to find optimal solutions to our complex, often unstructured problems

Our take

Developed as a fresh alternative to the archaic systems of data governance and information silos, Snowflake is a frictionless cloud data platform that removes the barriers preventing organizations of all sizes from unleashing the true value of their data.

The company equips organizations with a single, integrated platform that offers the only data warehouse built for the cloud; instant, secure and governed access to their entire network of data; and a core architecture to enable many types of data workloads, including a single platform for developing modern data applications.

Major competitors include Azure, SQL and AWS, and Snowflake has managed to keep ahead of the competition, cementing itself as a global force. Across its 1300+ partners, the company's cloud manages over 250PB of data (with more than 515 million data workloads running every day). Its continued focus on product R&D and partnership expansion have Snowflake well-positioned to manage itself amidst the competition.

Freddie

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 9 rounds)

Feb 2020

$479m

LATE VC

Oct 2018

$450m

LATE VC

Total funding: $1.4bn

Company benefits

Comprehensive health insurance plans
Health savings accounts
Robust retirement plans
Life and disability insurance
Weekly online lunch and learns
Virtual workout classes
Ergonomic work-from-home equipment
On-demand mental health and wellness programs
Fertility benefits and family planning resources
Generous time-off and various leave plans
Onsite and Remote Work
Employee discounts and pre-tax selections
New hire equity + Employee Stock Purchase Plan (ESPP)
Quarterly bonus or commission program

Company HQ

Bozeman, MT

Leadership

Benoit Dageville

(Co-Founder)

Benoit, a leading expert in parallel execution and self-tuning databases, founded Snowflake after 10+ years at Oracle as a lead architect. He holds a PhD in Computer Science and has 270+ patents.

Thierry Cruanes

(Co-Founder)

Thierry is a leading expert in query optimization and parallel execution. He has a PhD in Computer Science with a focus in Database Systems and is a named inventor on 200+ patents.

Sridhar Ramaswamy

(Chief Executive Officer)

Sridhar joined Snowflake in 2023 via the Neeva acquisition as SVP of AI and later became CEO. He co-founded Neeva and previously led Google’s Ads business, growing it from $1.5B to $100B.

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