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.
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Strategy:Wehelpour clients growth by achieving competitive advantage and creating value.
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To understand aging, we need to study the process by which individuals change over time: the diversity of phenotypic trajectories that individuals undergo as they age, and the causal factors that might underlie the variation. Rang is seeking a biostatistician to work on the design and modeling of longitudinal, preclinical experiments involving mouse and human cohorts with extensive genetic, multi-omic, and phenotypic data. You will be responsible for helping to design experiments, ensuring that they are well-constructed and adequately powered. You will also develop and implement novel statistical and machine learning techniques for analyzing the results of such experiments, both from in-house cohorts and from cohorts obtained from the outside. Your work will involve characterizing the trajectories of aging in phenotypic space; the identification of biomarkers involved in the aging process; and the use of statistical genetics to uncover the genetic factors that help give rise to these different trajectories. You will be working on a team encompassing diverse, cross-functional skills, which includes engineers, data scientists, biomedical scientists, and computational biologists.
- 4+ years of experience in statistical data analysis, including at least 2 years of hands-on work experience with real data (either in academia or in industry)
- Strong coding skills and substantial experience coding in at least one of R or Python
- Strong analytical and quantitative skills, including experience with state-of-the-art methods in applied statistics
- Significant experience with longitudinal data, time series analysis, survival analysis, or epidemiological modeling
- Experience in one or more of the following areas: statistical genetics (including the use of public annotation data such as dbSNP, ClinVar, the human phenotype ontology, or similar), causal modeling, and/or use of mass spectrometry data
- Track record of effective collaboration in a cross-functional environment with people of diverse backgrounds
- MS/PhD in Computer Science, Statistics, Biostatistics, Bioinformatics, or related technical field, or equivalent practical experience
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.