Senior Data Science Manager
Primary Location: United Kingdom, Remote Additional Locations: Denmark, Remote; Italy, Remote; Poland, Remote; Spain, Remote; Sweden, Remote; United Kingdom, Sheffield; United Kingdom, London Job ID R0000043258 Category Access Consulting
About this Role
We are looking for a candidate with strong computational, statistical, and biological capabilities and a demonstratedtrack recordof translating complex, multi-modal data into testable hypotheses and actionable insights in support of clinical development activities and decisions.
You will driveexploratoryand confirmatory analyses (both hypothesis-generating and hypothesis-driven), across diverse data types generated in drug development, including clinical trial data, genomics, proteomics, imaging, flow 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 related field) and1+ yearsof academic/industry experience;orMaster's Degreein a relevant quantitative field and3+ yearsof 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 andvalidatingstatistical and machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate outcomes
Experience in the application of AI/ML andproficiencyin Python, R, SQL, and cloud platforms (e.g., AWS, Azure, Databricks)
Familiarity with clinical trial design, drug development processes, and the role of biomarkers in regulatory and clinical decision-making
Perspective inleveraginginnovative approaches toexpeditedrug development and address the complexities of emerging data
Ability to work both independently and collaboratively, and to handle several concurrent, fast-paced projects
Strong problem-solving and collaboration skills, and rigorous and creative thinking
Excellent communication, data presentation, and visualization skills
Capable ofestablishingstrong working relationships across the organization
Preferred Qualifications
Experience withgenomics, proteomics, imaging, flow cytometry, or immunobiology datasetsfrom clinical trials is highly preferred
Experience withNLPis highly preferred
Experience withSurvival Analysisand time-to-event modeling is highly preferred
Experience withcausal ML and explainable AIis highly preferred
Knowledge of molecular biology and understanding of disease pathways is preferred
Experience with real-world data (RWD/RWE) 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 cloud-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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