Part of a team developing of ID Analytics advanced technologies in statistical score modeling, score model development and deployment, large scale database analysis and statistical algorithms.
Company: ID Analytics
Location: San Diego, CA
Interested applicants should visit
ID Analytics Careers page
to create an online profile and submit their resume for consideration.
The Principal Scientist will be part of a team responsible for the development of ID Analytics advanced technologies in statistical score modeling, score model development and deployment, large scale database analysis and statistical algorithms. The Principal Scientist will work independently on complex statistical score modeling and analysis problems with extremely large and complex data structures. This position requires working knowledge of business needs and the ability to work independently to design solution paths that achieve the needs of the customer without explicit guidance from business personnel.
Additionally, this position will provide technical leadership to other scientists within the organization. The Principal Scientist will provide technical leadership to other scientists within the organization. Assignments will include resolving problems or coordinating score model design architecture. Depending on the assignment, frequent client interaction may be necessary to complete the deliverables.
- Analysis, design, development, test, troubleshooting and documentation of complex data systems that may involve one or more of the following: predictive score models, feature extraction, data-driven analysis, machine learning, decision making and related utilities.
- Providing technical direction and guidance to internal teams regarding data discovery, planning and processing.
- Anticipate business needs and work proactively in improving data management tools and process.
- Identify and communicate trends and strategic directions in data management.
- Negotiate business requirements based on technical merits.
- Identify process improvement opportunities on internal processes and collaborate with developers to implement improvements.
- Provide regular status reports and input into product development and business development functions.
- Create and communicate R&D proposals based on the strategic vision of the company.
- Completing written documentation and reports of results. This will take the form of business reports, internal technology white papers and statistical system documentation.
- Technical leadership of other scientists and data analysts in problem design and building, evaluation and deployment of models and other analytical projects.
- Independent resolution of problems or coordinating score model design architecture, as well as designing robust and innovative technical solution approaches to complex analytical problems.
- Keep current with outside technical developments and inject new algorithms and techniques as appropriate.
- Other duties as assigned.
ID Analytics, Inc. is an Equal Opportunity Employer, M/F/D/V.
- Master's degree in a relevant technical discipline (Math, Engineering, Computer Science, Statistics or a similar field) with at least 8 years of job experience or Ph.D degree in a relevant technical discipline with at least 6 years of experience preferred.
- 5 years of experience with Object-Oriented programming languages, including familiarity with the use of Java for delivering high-speed, large scale data modeling solutions.
- 5 years of experience with Unix/Linux system architecture and command line tools.
- 5 years of experience with scripting languages.
- Experience with a statistical package such as SAS, R, SPSS or Weka.
- Demonstrated experience building advanced predictive models using very large data sets to solve complex business problems.
- Prior statistical score modeling and/or machine learning experience.
- Ability to simultaneously work across multiple projects, providing technical leadership on problem design and analysis.
- Strong interpersonal and communication skills (both written and oral) including the ability to communicate complex technical/statistical concepts to a non-technical audience.
- Fraud and risk management industry experience in developing scoring models from very large data sets is preferred.