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Full-Time

Principal ML Scientist

Confirmed live in the last 24 hours

Snowflake

Snowflake

5,001-10,000 employees

Data Cloud platform for data warehousing

Data & Analytics
AI & Machine Learning
Enterprise Software
Consulting

Senior, Expert

Dublin, CA, USA

Category
Applied Machine Learning
Natural Language Processing (NLP)
AI & Machine Learning
Required Skills
Python
Data Structures & Algorithms
SQL
Pandas
Natural Language Processing (NLP)
Requirements
  • 7+ years experience applying machine learning or statistical modeling on large datasets; pre-processing, data quality, feature engineering; the whole nine-yards
  • Deep understanding of the basic classes of ML algorithms, statistics & linear algebra; with a keen interest in the underlying theory & assumptions
  • Technical expertise in one or more of the following topics: Anomaly Detection, Clustering, Time-Series Analysis & Forecasting, Natural Language Processing (NLP), Uncertainty Quantification
  • Experience building LLM based applications in a business environment; up to date with advancements in the Gen-AI space, in an applied sense, about foundational models & tools in the ecosystem (such as langchain, RAGAS etc)
  • 7+ years experience writing production-quality, scalable code using Python. Expert software development lifecycle and best practices
  • Deep experience & a point-of-view for developing end-to-end turn key ML solutions, enablement & adoption baked into the solution
  • Expert level knowledge working with libraries such as scikit-learn, pandas, etc., SQL, Airflow, Cloud Services
  • Required to adapt quickly to changing project scope while delivering value.
Responsibilities
  • Lead projects; Conceptualize, design and lead the execution of large ML projects, aligning with the business goals, delivering measurable value & impact.
  • Engage with stakeholders; lead the conversations with technical & non-technical stakeholders; identify areas where one can apply AI & ML; facilitating discussions around key drivers for decision making & operational efficiencies.
  • Provide technical & thought leadership; designing and implementing advanced machine learning techniques, focusing on robust & scalable solutions. Participate in all stages of development, ideation to production.
  • Provide mentorship; to junior ML & Data Scientists, around problem formulation, technical design, algorithm choices & code quality.
  • Develop hands-on; analyze large amounts of data, manage data quality, design & develop complex ML models (and the ensuing ML solutions), deploy & manage production-grade applications end-to-end, tell the story in a compelling manner.
  • Partner with customers; showcase internal solutions to customers, help them envision solutions stringing Snowflake platform capabilities together, partner with internal teams that enable customer solutions.

Snowflake offers a Data Cloud platform for data warehousing, data lakes, and data application development, enabling secure sharing of governed data across multiple public clouds. The platform supports diverse analytic workloads with near-unlimited scale and performance.

Company Stage

IPO

Total Funding

$2.5B

Headquarters

Bellevue, Washington

Founded

2012

Growth & Insights
Headcount

6 month growth

5%

1 year growth

7%

2 year growth

38%
Simplify Jobs

Simplify's Take

What believers are saying

  • Snowflake's continuous innovation and feature expansion, as seen in their Data Cloud World Tour, promise robust career growth opportunities.
  • The company's strategic investments and acquisitions indicate strong financial health and a commitment to staying at the forefront of data technology.
  • Collaborations with companies like Solaris and Omnata highlight Snowflake's influence and integration capabilities across various industries.

What critics are saying

  • The rapid pace of acquisitions and integrations may lead to operational challenges and cultural misalignment.
  • Intense competition in the cloud data platform market from giants like AWS and Google Cloud could pressure Snowflake's market share.

What makes Snowflake unique

  • Snowflake's focus on democratizing data access and analytics sets it apart from traditional data platforms.
  • Strategic investments in AI-driven startups like Metaplane enhance Snowflake's data quality and reliability, providing a competitive edge.
  • Acquisitions such as Samooha and Ponder expand Snowflake's capabilities in data clean rooms and Python integration, respectively.

Benefits

We've got your back - We offer comprehensive health insurance plans, health savings accounts, robust retirement plans, and generous life and disability insurance.

A Balanced Lifestyle - All Snowflakes have access to our weekly online lunch and learns, virtual workout classes, and ergonomic work-from-home equipment. We offer on-demand mental health and wellness programs to support our employees and their families.

Your People Matter - Help offset the cost of growing your family with our fertility benefits and family planning resources. Count on our generous time-off and various leave plans for you to rest, refuel, and sustain a great work-life balance.

Global Snowflake Team - No matter where you are in the world, we will get you connected and supported with a work-from-home setup.

Treat Yourself - Personalize your Snowflake benefits by tapping into our employee discounts and pre-tax selections.

Invest In Your Future - Eligible employees enjoy new hire equity, Employee Stock Purchase Plan (ESPP), and a quarterly bonus or commission program.