Risk Prevention Data Scientist Volunteer Forest Fire Prevention Derivatives, CrowdDoing,

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• Risk Prevention Data Scientist Volunteer Forest Fire Prevention Derivatives, CrowdDoing,
• See more detailed background on CrowdDoing's forest fire prevention derivatives
• https://drive.google.com/file/d/1dBp_HUr-tCCNaeGoSDfPrirRPbaoV3X4/view?usp=sharing

Risk Prevention Data Scientist Volunteer Forest Fire Prevention Derivatives, CrowdDoing,
Bobby Fishkin, lead author

In 2018, Sacramento was named the "the Most Polluted City on Earth" due to "smoke from Camp Fire," This proposal aims to prevent that from happening again through adopting a systemic approach and collaborating with stakeholders to actively prevent future such events. The insurance industry, along with institutional chief risk officers, have begun to recognize the importance of moving from "loss compensation to loss prevention."

CrowdDoing and Project Heather propose launching a prevention derivative with two new stakeholders: (a) contingent payers who pay in proportion to the reduction in risk, and (b) impact investors who finance social innovations in which their return is similarly proportional to the reduction in risk. It will build on existing precedents for contingent contracts involving social- innovation-based risk prevention.

Risk Prevention Data Scientist Volunteer Forest Fire Prevention Derivatives, CrowdDoing, Duties and Responsibilities

• Managing analytics database
• Implementing processes that improve and lead to greater data quality
• Conducting statistical analyses to develop strategies
• Documenting all processes and research
• Building new algorithms and model training
• Executing projects involving analytics
• Identifying data patterns and trends
• Analyzing data to develop predictive models
• Creating, managing, and maintaining analytically rigorous data
• Noting anomaly detection and running diagnostics
• Performing graphical model analysis
• Possessing a solid machine learning foundation
• Participating in software-focused marketing efforts

Risk Prevention Data Scientist Volunteer Forest Fire Prevention Derivatives, CrowdDoing, Requirements and Qualifications

• Expert in statistical modeling/data mining
• Experienced with SQL Server
• Experienced in data analysis, predictive modeling, and data mining techniques
• Able to analyze problems and strategize for better solutions
• Excellent verbal and written communication skills
• Able to multitask, prioritize, and manage time effectively
• Comfortable in both a leadership and team-player role
• Creative problem solver who thrives when presented with a challenge
• Goal-oriented, organized team player
• Encouraging to team and staff; able to mentor and lead
• Bachelor’s degree in computer science, engineering, mathematics or related field; Master’s degree in computer science, mathematics or related field preferred
• Four years of relevant industry experience
• Strong familiarity and hands-on experience with SQL and statistical software packages (Python, R, SAS)
• Knowledge of tools and techniques in machine learning
• Expert in relational database design and concepts
• Expert in one or more programming languages (C/C++, Python, Perl, Java)
• Experience in genetic algorithms, logistic and linear regression, PCA, decision tree analysis and statistical methods
• Up-to-date on latest industry trends; able to articulate trends and potential clearly and confidently
• Good interpersonal skills and communication with all levels of management
• Able to work in a fast-paced environment

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