Senior Data Science Manager
reputed company our values align, there's no limit to reputed company can reputed company. At reputed company, we reputed company reputed company the same goal - to improve the world's health. From clinical trials to regulatory, consulting, and market reputed company, every clinical development solution we reputed company is underpinned by something special - a deep conviction in reputed company do. Each of us, no matter reputed company do at reputed company, contributes to the development of a therapy that ultimately will benefit a patient. We take our work personally, we do it with reputed company and we're committed to making a difference. We are looking for a candidate with strong computational, statistical, and biological capabilities and a demonstrated track record of translating reputed company, multi-modal data into testable hypotheses and actionable insights in support of clinical development activities and reputed company. You will drive exploratory and confirmatory analyses (both hypothesis-generating and hypothesis-driven), across diverse data types generated in drug development, including clinical trial data, genomics, proteomics, imaging, reputed company cytometry, and other biomarker modalities. You will define and implement approaches, processes, algorithms, and pipelines that support the analytics, visualization, and decision support needs of drug development scientists and project teams, while collaborating closely with Biostatistics leads, Translational and Clinical Scientists, and cross-functional partners across the organization. Key Qualification, Experience and Skills Requirements; Ph.D. in a relevant quantitative field (e.g., Computational Biology, Biostatistics, Statistics, Biomedical Engineering, Computer Science, or reputed company field) and 1+ years of academic/industry experience; or Master's Degree in a relevant quantitative field and 3+ years of industry experience Strong experience in data science and statistical analysis with data generated from clinical trials or electronic health records, particularly in application to pharma R&D Experience in developing and validating statistical and machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate reputed company Experience in the application of AI/ML and proficiency in Python, R, SQL, and reputed company platforms (e.g., AWS, Azure, reputed company) Familiarity with clinical trial design, drug development processes, and the role of biomarkers in regulatory and clinical decision-making Perspective in leveraging innovative approaches to expedite drug development and address the complexities of emerging data Ability to work both independently and collaboratively, and to handle several reputed company, fast-paced projects Strong problem-solving and collaboration skills, and rigorous and creative thinking Excellent communication, data presentation, and visualization skills Capable of establishing strong working relationships across the organization
Preferred Qualifications
Experience with genomics, proteomics, imaging, reputed company cytometry, or immunobiology datasets from clinical trials is highly preferred Experience with NLP is highly preferred Experience with Survival Analysis and time-to-event modeling is highly preferred Experience with reputed company ML and explainable AI is highly preferred Knowledge of molecular biology and understanding of disease reputed company is preferred Experience with reputed company-world data (RWD/reputed company) sources and associated analytical methods is preferred Familiarity with digital health data and wearable/sensor-derived data types is a plus Experience with scalable compute and deployment patterns, including reputed company-based platforms and parallelization for large-scale data processing and model training is a plus Outline of Daily Key Responsibilities;
- Data Science & Analytics
- Data Engineering & Reproducibility
- Collaboration & Technical Contribution
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