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November 20, 2023
Guidewire Software Logo

2024 Machine Learning Engineer Summer Intern

Guidewire Software,

San Mateo, CA

This is an old job. It may expired or is no longer available.

The employer may not accept applications or may not be hiring.

Guidewire is searching for a unique individual who is ambitious, curious, and hungry for a rare chance to transform a 500-year-old industry from the inside out.  Through our data listening capabilities, we collect more data (and more important data) than any other company in our market.  We seek ways to make sense of it, showcase it, and transform it into insight that feeds billions of decision points every year across pricing, portfolio management, underwriting, claims management, and risk transfer.
 
At Guidewire, we offer a combination of good working conditions, an excellent market opportunity, a rational and meritocratic company culture, quality software products, and a long history of careful hiring have allowed us to create an enviable work environment.
 
Guidewire Analytics helps insurers and other financial institutions to model new and evolving risks such as cyber. By combining internet-scale data listening, adaptive machine learning, and insurance risk modeling, Guidewire Analytics insights help P&C customers face new risks, take advantage of new opportunities and develop new products.

What will I be doing?

    • Guidewire is offering a 3-month internship in the Guidewire Analytics team. The internship is designed to give an opportunity to work in a real-world business environment, and to take responsibility for a specific data project that has the potential to provide real value to our customers.
    • Our teams tackle a wide variety of interesting problems in the Property & Casualty insurance industry. On this team you will be exposed to a wide variety of problems and projects including the following:
    • Explore ways to enhance our data science on modeling processes by exploring novel techniques the creation of models that help with our classification and computational problems
    • Expand our internet-scale data listening capabilities by implementing new data sources or extending core API functionality
    • Contribute to our efforts to build out our MLOps capabilities and enhance our ability to accelerate ML development and deliver reproducible, testable, and rapidly evolving capabilities to customers
    • You will be mentored by experienced data scientists and modelers and exposed to advanced ML techniques and approaches. You will have the opportunity to learn more about the exciting world of Cybersecurity and Cyber Risk quantification. You will be writing Python code, wrangling data from a range of sources and building models.

Intern Requirements:

    • Currently pursuing (or just finished) bachelor's or Master's (graduating in 2024-2025; Master's preferred) studies in a Computer Science, Engineering, Mathematics, or related field.
    • Demonstrate knowledge of:
    • Python coding, in particular, data manipulation
    • Ability to work independently on a project and as part of a team. 
    • Define, model, and solve real-world, ambitious, insurance problems using various data-driven approaches
    • Design and implement tools and frameworks to be used across various machine learning and data science teams
    • A strong desire to help build components of our Machine Learning platform that will be used by internal and external Guidewire customers.
    • Preferred Qualifications:
    • Operational knowledge of Git, Docker, Linux.Strong understanding of various Transformer model architectures (decoder only, Encoder-Decoder, Encoder Only).
    • Ability to discuss trade-offs and perform independent research
    • Knowledge of Amazon AWS services such as EC2, EMR, S3, SageMaker, EKS.

Other types of things that we like to cultivate:

    • Curiosity based on genuine love of technology and analytics
    • Accountability based on an earnest desire to do what is expected without prompting
    • Kindness and respect for your fellow teammates
$40 - $40 an hour

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