Our Profession is our Passion! We atRangTechnologiesspecialize in planning, implementing, managing, and staffing InformationTechnology Solutionsand Services. Our goal is to help our clients define their investments in technology, optimize processes that bring fast-track success, and deliver business-critical applications to improve performance. We value diversity. We operate as one team, bringing highly qualified and experienced software and management professionals with advanced degrees in Computer Science, Management, Engineering, Statistics and Bioinformatics.
The values that drive our success are:
Strategy:Wehelpour clients growth by achieving competitive advantage and creating value.
Quality:We believe in Quality First and Quality Must in solutions we deliver.
Support:We bring ideas and talent to empowerbusiness performancewith new-age technologies.
We take pride inbuildingstrategiclong-term relationship with our clients.
- Write SAS programs to generate tables, listings and figures
- Identify data issues and report findings to the appropriate team members
- Assist with statistical quality assurance review and program validation
- Interact with other members of the Statistical Programming
- Exceptional Communicator, able to quickly read and write technical specifications and documentation
- Understanding of SAS clinical terminology and programming.
- Experience with SAS or any other statistical software package preferred
- Bachelors degree in statistics, mathematics, engineering or life science related field, Masters' preferred but not required
Work Authorization Status:
- US Citizens and Permanent Residents
- Any EAD including H4, J2, L2
- F1-OPT/CPT; E-Verified and Support for OPT Extensions
- H1 Visa and GC sponsorship
- TN Visa for Canadian Citizens
- E3 Visa for Australian Citizens
All your information will be kept co-MS in Finance, Financial Engineering, Analytics or Mathematics, Computer Science, Statistics, Industrial Engineering, Operations research, or related field.
-Good understanding of Probability of Default (PD), LGD and EAD modeling technique.
-Very good understanding of Predictive modeling techniques and their application.
-Knowledge of Credit life cycle.
-Statistics and machine learning techniques.
-Conducted and applied statistical methodologies including linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, cluster analysis
-Team player and collaboration skills.
-Programming skills in R, SAS, and PYTHON.
-Fluency with Excel, PowerPoint and Word
-Strong written and oral presentation / communication skills must have the ability to convey complex information simply and clearly
nfidential according to EEO guidelines.