Sr. Data Science Manager

• Takes ownership and executes on more complex and often vague business challenges involving data science. Succeeds in specialized projects by scoping, defining measures of success, utilizing a data science vision for project success, and exceeding on prescribed and some vague timelines. Executes and leads broad projects independently with a sense of urgency. Utilizes specialized knowledge of consumer analytics including retention models, agency economics, and leads optimization in their daily work.
• Utilizes broad knowledge of advanced programing, complex ETL and specialized modeling methods to execute projects and leads the team through examples of effective technical skills. Demonstrates clean reusable code and effective documentation, encourages others to do the same. Acts as the main contributor to multiple phases of a data science project (ideation, experiment design, EDA, feature engineering, model building, deployment, etc. ). Utilizes a strong sense of ownership and contributes to multiple tasks and deadlines simultaneously.
• Partners closely with IT, business, and data management/engineering teams to understand, utilize, and improve our data infrastructure. Advises on complex matters and serves as an objective and transparent partner to drive fact-based decision making and a measures of success culture. Provides strategic direction, project clarity and methodological consultation. Delivers results both individually and by mentoring and empowering other team members.
• Mentors and provides guidance to team members. Provides high level coaching and knowledge around technical and non-technical skills. Reviews AI/ML modeling, statistical analysis, and data analysis completed by other team members, providing coaching and feedback as needed.
• Develops presentations and presents to all groups and levels of leadership, including executives. Regularly communicates complex technical material understandable to non-technical associates.
• Manages specialized model deployments via MLOps techniques. Partners closely with analytics and IT teams to deploy models/rules in various platforms and leads testing of new solutions. Takes active role in steering MLOps environment improvements.

• Minimum seven years of work experience required in data analysis, statistical or mathematical modeling, or related.

• High School Diploma or equivalent required.
• Masters degree required in data science, statistics, mathematics, business analytics or related.

• Strong verbal communication and listening skills. Advanced storytelling skills with ability to communicate complex data insights clearly to technical and non-technical audiences.
• Demonstrated written communication skills.
• Proficient in Microsoft Office Suite.
• Develops and delivers effective presentations.
• Effectively coaches and delivers constructive feedback.
• Demonstrated problem solving skills.
• Excellent collaboration and team building skills.
• Ability to influence internal and/or external constituents.
• Seeks to acquire knowledge in area of specialty.
• Possesses flexibility to work in a fast paced, dynamic environment. Able to meet deadlines and priorities that shift with business needs. Able to simultaneously handle multiple priorities. Possesses solid project management skills.
• Demonstrated analytical skills. Possesses advanced technical aptitude.
• Advanced proficiency working on large-scale structured and unstructured multidimensional data using advanced knowledge of open-source cloud-enabled analytical programming languages. Advanced ability to consult on data extraction, data manipulation and data design for statistical, modeling and monitoring needs. Advanced knowledge of data analysis, manipulation tools (SQL, Python, SAS, R, and/or Snowflake) and cloud computing services (AWS). Advanced knowledge of data visualization tools (example, Tableau, Power BI).
• Advanced proficiency in using explanatory, diagnostic, and inferential techniques such as experimental design, hypothesis testing, clustering analysis, time series and other statistical modeling algorithms with the ability to decide the appropriate methodology for the purpose. Advanced proficiency in predictive and prescriptive modeling using advanced machine learning and deep learning techniques. Advanced in ML/AI model deployment best practices. Able to adapt quickly to new technologies. Advanced knowledge of coding standards and version control (Git). Other. Broad knowledge of data ethics and data privacy.

• Farmers offers a competitive salary commensurate with experience, qualifications and location.

• 401(k)
• Medical
• Dental
• Vision
• Health Savings and Flexible Spending Accounts
• Life Insurance
• Paid Time Off
• Paid Parental Leave
• Tuition Assistance
• For more information, review “What we offer” on

Farmers Insurance