Senior Associate Data Scientist

Farmers Insurance•Los Angeles, CA

12d•$120,409•Hybrid

About The Position

Farmers Group (Woodland Hills, CA) seeks a Senior Associate Data Scientist to apply analytics and modeling techniques to improve business results, perform routine assignments, leverage customer information and behavioral data to influence strategic business decisions while using analytics, multi-variate models, machine learning and data mining technologies. Specific duties include: execute on standard business challenges involving data science, succeed in projects by scoping, defining measures of success, utilizing a data science vision for project success, and accomplishes successfully within prescribed timelines, execute on routine projects with a sense of urgency (30%); utilize conceptual knowledge of consumer analytics including retention models, agency economics, and lead optimization in their daily work, utilize basic knowledge of programing, ETL and modeling methods to execute projects and assists the team through examples of good technical skills (40%); partner closely with IT, business, and data management/engineering teams to understand, utilize, and improve data infrastructure, advise on general matters and serve as an objective and transparent partner to drive fact-based decision making and a measures of success culture (10%); contribute to development of presentations and presents to leadership, occasionally communicate complex technical material understandable to non-technical associates and prepare documentations for regulatory communications (10%); execute basic to intermediate model deployments via established MLOps techniques and work with analytics and IT teams to test and deploy models 10%). Option to work remotely with required travel to local offices as needed, if within 50 miles of remote worksite.

Requirements

Bachelor’s degree, or foreign equivalent, in Statistics, Business Economics and Statistics, or a closely related field of study.
3 years of experience in the job offered, or as a Product Analyst, Predictive Analyst, or similar position applying analytics and modeling techniques in the insurance industry.
3 years of experience communicating complex data insights to both technical and non-technical audiences.
3 years of experience influencing internal and external stakeholders.
3 years of experience working with large-scale structured and unstructured multidimensional data using open-source, cloud-enabled analytical programming languages.
3 years of experience consulting on data extraction, manipulation, and design for statistical, modeling, and monitoring purposes.
3 years of experience performing data analysis and manipulation using SAS, Python, SQL, and Snowflake, as well as Generalized Linear Model (GLM) modeling.
3 years of experience creating data visualizations using Tableau and Power BI.
3 years of experience applying explanatory, diagnostic, and inferential techniques, including experimental design, hypothesis testing, clustering analysis, and Generalized Linear Modeling.
3 years of experience selecting appropriate methodologies and techniques suited to the analytical objective.
3 years of experience developing predictive and prescriptive models using advanced machine learning and deep learning techniques.
3 years of experience implementing ML/AI model deployment best practices.
1 year of experience adhering to coding standards and using version control with Git.
1 year of experience preparing documents for regulatory communications.

Responsibilities

Execute on standard business challenges involving data science.
Succeed in projects by scoping, defining measures of success, utilizing a data science vision for project success, and accomplishing successfully within prescribed timelines.
Execute on routine projects with a sense of urgency.
Utilize conceptual knowledge of consumer analytics including retention models, agency economics, and lead optimization in their daily work.
Utilize basic knowledge of programming, ETL and modeling methods to execute projects and assist the team through examples of good technical skills.
Partner closely with IT, business, and data management/engineering teams to understand, utilize, and improve data infrastructure.
Advise on general matters and serve as an objective and transparent partner to drive fact-based decision making and a measures of success culture.
Contribute to the development of presentations and present to leadership.
Occasionally communicate complex technical material understandable to non-technical associates.
Prepare documentations for regulatory communications.
Execute basic to intermediate model deployments via established MLOps techniques.
Work with analytics and IT teams to test and deploy models.