Skip to content
Analytic Science Lead Scientist
| Company | FICO |
|---|
| Location | San Diego, CA, USA |
|---|
| Salary | $120000 – $189000 |
|---|
| Type | Full-Time |
|---|
| Degrees | Master’s |
|---|
| Experience Level | Senior, Expert or higher |
|---|
Requirements
- MS degree in Statistics, Engineering, Mathematics, Computer Science, Physics, or Operations Research field (PhD preferred)
- Some related industry experience in predictive modeling and data mining
- Experience with Python, C, C++, Java, SQL, or Perl, along with a strong understanding of basic software design principles, coding standards, and best practices
- Experience analyzing large datasets, with a focus on Hadoop, Spark, and Spark SQL technologies
- Skilled in applying data-cleaning techniques and performing statistical analyses to understand dataset structures
Responsibilities
- Analyze large amounts of real-world data and ensure data quality throughout all stages for acquisition and processing, including data collection, normalization and transformation
- Evaluate suitability for modeling, data clean-up and filtering, pattern identification and variable creation
- Select sampling criteria and generate performance definitions and variables
- Perform experiments with different types of algorithms and models, analyzing performance to identify the best algorithms to employ
- Contribute to enabling execution of next generation consortium and custom fraud detection models on the FICO Platform
- Assist with model go-lives by performing production data validations and score distribution analysis of models in production
- Assist with client meetings to investigate and resolve problems
- Apply data mining methodology in thorough analysis of model behavior and provide support for customer meetings, model construction and pre-sales
- Manage projects under time and resource constraints while working with other teams within FICO (Software, IT, Product Management, and Product Support) to provide high quality support to enable integration and deployment of analytics software and solutions
- May participate in post-implementation support
Preferred Qualifications
- Knowledge of one or more of the following is preferred: Bayesian networks, PCA, independent component analysis, linear and logistic regressions, inference, estimation, experimental design, neural networks, SVM
