Senior Decision Scientist
New
F
Farmers InsuranceInsurance analytics
Workable workplace: remote; Workable locations: Brazil. MexicoFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Fluent English, both written and spoken.
- Required Skills
- PythonSQLMicrosoft SQL ServerSnowflakeR
Requirements
- Experience in data analytics, decision science, statistics, or a related quantitative field.
- Bachelor's degree in Data Science, Statistics, Mathematics, Business Analytics, or a related field; a master's degree is preferred.
- Strong knowledge of statistical analysis and quantitative methodologies.
- Advanced experience with exploratory data analysis (EDA).
- Understanding of experimental design and hypothesis testing.
- Knowledge of causal inference techniques.
- Experience with distribution analysis, correlation, outlier detection, multivariate analysis, time series, and machine learning concepts.
- Ability to interpret complex datasets and translate findings into actionable recommendations.
- Python and/or R experience for statistical programming and data analysis.
- SQL experience, preferably with Snowflake or Microsoft SQL Server.
- Experience with data integration, transformation, and quality validation.
- Experience using Excel and Power BI for data analysis and visualization.
- Fluent English, written and spoken.
- Demonstrated experience independently managing analytical projects and working with business stakeholders.
Responsibilities
- Lead analytical projects from understanding business challenges through solution development and presentation of recommendations.
- Apply statistical and quantitative methods to large datasets to identify trends, patterns, correlations, and business opportunities.
- Conduct exploratory data analysis, hypothesis testing, experimental design, and causal inference.
- Build descriptive and explanatory models or use outputs from predictive models to address business challenges.
- Use Python and/or R for advanced data analysis.
- Extract, integrate, transform, and validate data from multiple sources.
- Partner with business stakeholders to translate strategic objectives into analytical solutions.
- Communicate analytical findings through visualizations, presentations, and business recommendations.
- Collaborate with data science, data engineering, IT, and other technical teams to improve data quality and analytical processes.
- Support deployment and monitoring of predictive models in business workflows.
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