Senior Data Scientist
Guidewire Software, Inc.
Guidewire-Cyence is searching for a Senior Data Scientist to join us on our mission to transform cyber-insurance with the industry's leading cyber risk platform. Cyber is the #1 threat to US national security, above nuclear weapons, and our work here makes a meaningful impact in this space! You will report to the Director of Risk Modeling..
Who We Are, What We Believe, & What We Build
Guidewire is the AWS of insurance. As the market leader, 540 insurance companies run on our mission-critical platform. Every second, we support underwriters crafting policies and agents settling claims. We believe that making a great decision should not require 100 in-house data scientists. Our products range from cyber risk quantification to potent ML sandboxes. We are a post-IPO company with the vision to redefine insurance.
Who You Are
You are a passionate, detail-oriented, and creative problem solver with a strong background in Data Science and ML Engineering, excited by the prospect of pursuing hard problems and exploring the unknown, and passionate about the end-to-end lifecycle of modeling. You are inspired by working as a full-stack data scientist. You enjoy applying advanced quantitative methods such as statistical modeling, machine learning algorithms, numerical simulations, and optimization techniques to analyze complex datasets, build predictive models, and write production code. Experience in catastrophe modeling is a plus!ResponsibilitiesDevelop, calibrate, validate, and deploy for production cyber risk models for the (re)insurance and financial services markets.Develop and implement methodologies to quantify the financial impact of cyber risk on single entities as well as large insured portfolios.Develop and implement tools to effectively visualize the potential impact of cyber events.Explore different data sources to come up with features and assumptions to enhance our set of probabilistic risk models.Integrating/automating modeling processes in our production pipeline to feed our platform.Define and implement a globally consistent best practice process for data validation, feature selection, and modeling of catastrophe exposures.Champion best practices to design and extend a rapid and flexible modeling framework.Communicate results to internal and external stakeholders.Engage and collaborate directly with clients on a deep technical level.Collaborate with other leaders across the Analytics organization, including Product Management, Engineering, and Client Engagement.Qualifications and RequirementsPhD or MS degree in Computer Science, Applied Mathematics, Statistics, Engineering, or similar quantitative disciplines.Mastery in developing and maintaining end-to-end data and modeling pipelines using AWS Glue, Airflow, and Sagemaker.Strong programming skills in Python and fluency in data manipulation(SQL, pandas, pyspark) and Machine Learning(Scikit-learn, statsmodel, XGBoost and etc) tools.Experience working with AWS (or similar) tools/services like Athena, S3, EC2, Redshift, etc.5+ years of experience in statistical data analysis, feature engineering, predictive modeling, and data visualizationTrue passion for leading, inspiring, mentoring, and attracting world-class colleagues.Experience working with different types of datasets (e.g., unstructured, semi-structured, with missing information).Excellent written and verbal communication skills.Ability to think critically and creatively in a dynamic environment, while picking up new tools and domain knowledge along the way.A positive attitude and a growth mindset.$160,000 - $175,000 a yearOur salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.#LI_Remote#LI-PN1#feature#datascientist #predictivemodeling #
About Guidewire
Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently. We combine digital, core, analytics, and AI to deliver our platform as a cloud service. More than 540+ insurers in 40 countries, from new ventures to the largest and most complex in the world, run on Guidewire.
As a partner to our customers, we continually evolve to enable their success. We are proud of our unparalleled implementation track record with 1600+ successful projects, supported by the largest R&D team and partner ecosystem in the industry. Our Marketplace provides hundreds of applications that accelerate integration, localization, and innovation.
For more information, please visit and follow us on Twitter: .
Guidewire Software, Inc. is proud to be an equal opportunity and affirmative action employer. We are committed to an inclusive workplace, and believe that a diversity of perspectives, abilities, and cultures is a key to our success. Qualified applicants will receive consideration without regard to race, color, ancestry, religion, sex, national origin, citizenship, marital status, age, sexual orientation, gender identity, gender expression, veteran status, or disability. All offers are contingent upon passing a criminal history and other background checks where it's applicable to the position.
Disability Accommodations and Guidewire’s Appeals Process. Guidewire provides accommodations to the hiring process to create a fair opportunity for candidates with disabilities to contend for open positions. Accommodation requests should be directed to . If things do not go as hoped, we invite you to use our appeals process. Guidewire promises to independently review any denied accommodation and any decision not to offer you the position. The appeals process is the same in either case. Within five business days of receiving a notice of denial of an accommodation, or receiving a notice of your non-selection for a vacancy, e-mail to make an appeal. Guidewire will assign a new decision-maker to review the request and/or hiring decision, who will then notify you in writing of a decision within 10 business days.
Who We Are, What We Believe, & What We Build
Guidewire is the AWS of insurance. As the market leader, 540 insurance companies run on our mission-critical platform. Every second, we support underwriters crafting policies and agents settling claims. We believe that making a great decision should not require 100 in-house data scientists. Our products range from cyber risk quantification to potent ML sandboxes. We are a post-IPO company with the vision to redefine insurance.
Who You Are
You are a passionate, detail-oriented, and creative problem solver with a strong background in Data Science and ML Engineering, excited by the prospect of pursuing hard problems and exploring the unknown, and passionate about the end-to-end lifecycle of modeling. You are inspired by working as a full-stack data scientist. You enjoy applying advanced quantitative methods such as statistical modeling, machine learning algorithms, numerical simulations, and optimization techniques to analyze complex datasets, build predictive models, and write production code. Experience in catastrophe modeling is a plus!ResponsibilitiesDevelop, calibrate, validate, and deploy for production cyber risk models for the (re)insurance and financial services markets.Develop and implement methodologies to quantify the financial impact of cyber risk on single entities as well as large insured portfolios.Develop and implement tools to effectively visualize the potential impact of cyber events.Explore different data sources to come up with features and assumptions to enhance our set of probabilistic risk models.Integrating/automating modeling processes in our production pipeline to feed our platform.Define and implement a globally consistent best practice process for data validation, feature selection, and modeling of catastrophe exposures.Champion best practices to design and extend a rapid and flexible modeling framework.Communicate results to internal and external stakeholders.Engage and collaborate directly with clients on a deep technical level.Collaborate with other leaders across the Analytics organization, including Product Management, Engineering, and Client Engagement.Qualifications and RequirementsPhD or MS degree in Computer Science, Applied Mathematics, Statistics, Engineering, or similar quantitative disciplines.Mastery in developing and maintaining end-to-end data and modeling pipelines using AWS Glue, Airflow, and Sagemaker.Strong programming skills in Python and fluency in data manipulation(SQL, pandas, pyspark) and Machine Learning(Scikit-learn, statsmodel, XGBoost and etc) tools.Experience working with AWS (or similar) tools/services like Athena, S3, EC2, Redshift, etc.5+ years of experience in statistical data analysis, feature engineering, predictive modeling, and data visualizationTrue passion for leading, inspiring, mentoring, and attracting world-class colleagues.Experience working with different types of datasets (e.g., unstructured, semi-structured, with missing information).Excellent written and verbal communication skills.Ability to think critically and creatively in a dynamic environment, while picking up new tools and domain knowledge along the way.A positive attitude and a growth mindset.$160,000 - $175,000 a yearOur salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.#LI_Remote#LI-PN1#feature#datascientist #predictivemodeling #
About Guidewire
Guidewire is the platform P&C insurers trust to engage, innovate, and grow efficiently. We combine digital, core, analytics, and AI to deliver our platform as a cloud service. More than 540+ insurers in 40 countries, from new ventures to the largest and most complex in the world, run on Guidewire.
As a partner to our customers, we continually evolve to enable their success. We are proud of our unparalleled implementation track record with 1600+ successful projects, supported by the largest R&D team and partner ecosystem in the industry. Our Marketplace provides hundreds of applications that accelerate integration, localization, and innovation.
For more information, please visit and follow us on Twitter: .
Guidewire Software, Inc. is proud to be an equal opportunity and affirmative action employer. We are committed to an inclusive workplace, and believe that a diversity of perspectives, abilities, and cultures is a key to our success. Qualified applicants will receive consideration without regard to race, color, ancestry, religion, sex, national origin, citizenship, marital status, age, sexual orientation, gender identity, gender expression, veteran status, or disability. All offers are contingent upon passing a criminal history and other background checks where it's applicable to the position.
Disability Accommodations and Guidewire’s Appeals Process. Guidewire provides accommodations to the hiring process to create a fair opportunity for candidates with disabilities to contend for open positions. Accommodation requests should be directed to . If things do not go as hoped, we invite you to use our appeals process. Guidewire promises to independently review any denied accommodation and any decision not to offer you the position. The appeals process is the same in either case. Within five business days of receiving a notice of denial of an accommodation, or receiving a notice of your non-selection for a vacancy, e-mail to make an appeal. Guidewire will assign a new decision-maker to review the request and/or hiring decision, who will then notify you in writing of a decision within 10 business days.
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