About this role
This role applies advanced analytics to clinical development processes, with a focus on feasibility of AbbVie clinical trials across program, study, country, and site levels. You will create fit-for-purpose analyses, generate analytics-driven site lists, and support KPI and reporting needs while ensuring compliance with relevant regulations and GCP standards.
Key Responsibilities
- Enable fit-for-purpose analytics solutions for assigned projects
- Conduct and deliver clinical trial feasibility analysis (study design, benchmarking, country and site selection, competitive landscape)
- Generate machine learning or quantitatively informed site lists
- Leverage statistical methodologies and recommend additional techniques
- Ensure compliance with federal/local regulations, GCPs, ICH Guidelines, and AbbVie SOPs
Technical Overview
You will perform statistical analysis and data mining using Excel, SQL, R, and Python, and communicate results through visualization tools such as Tableau or Power BI. The technical scope includes feasibility analysis, study benchmarking, and machine learning or quantitatively informed site list generation under Good Clinical Practices (GCPs) and ICH Guidelines.
Ideal Candidate
The ideal candidate is a mid-level Data Scientist with 2-3 years of data science and analytics experience focused on clinical trial feasibility and real-world data sources. They have strong statistical and data mining expertise and can deliver fit-for-purpose analytics using Excel, SQL, R, and Python, with Tableau or Power BI for visualization.
Must-Have Skills
Bachelor's degree statisticsanalyticsbioinformaticsdata science or equivalent field2-3 years of Data science and analytics-related experienceComplete or Full / Career proficiency in ExcelSQLRPython and/or other statistical packagesIntermediate-level knowledge of statistical and data mining techniquesIntermediate proficiency with visualization tools like TableauPower BI or equivalentdemonstrated effective communication skillsdomain knowledge in clinical trial feasibility and real-world data sourcesadherence to federal regulations and applicable local regulationsGood Clinical Practices (GCPs)ICH GuidelinesAbbVie Standard Operating Procedures (SOPs)
Nice-to-Have Skills
Master's degreeExperience with Machine Learning and other advanced analytics techniques preferred
Tools & Platforms
ExcelSQLRPythonTableauPower BIGood Clinical Practices (GCPs)ICH GuidelinesAbbVie Standard Operating Procedures (SOPs)
Required Skills
fit-for-purpose analytics solutionsclinical trial feasibilitystudy designstudy benchmarkingcountry and site selectionMachine Learningstatistical methodologiesExcelSQLRPythonTableauPower BIstatistical and data mining techniquesKPIsGood Clinical Practices (GCPs)ICH GuidelinesAbbVie Standard Operating Procedures (SOPs)
Hard Skills
statistical methodologiesGood Clinical Practices (GCPs)ICH GuidelinesExcelSQLRPythondata mining techniquesstatistical and data mining techniquesTableauPower BIvisualization toolsMachine Learningquantitatively informed site listsfit-for-purpose analytics solutionsclinical trial feasibilitystudy designstudy benchmarkingcountry selectionsite selection insightscompetitive landscapestatistical analysesKPIsfederal regulationslocal regulationsAbbVie Standard Operating Procedures (SOPs)experiments and recommending additional techniques
Soft Skills
cross-functional team collaborationeffective communication skillscommunicate analytical and technical concepts in layman's termsproblem-solving skillsanalytical skillssuccessful execution in a fast-paced environmentmanaging multiple priorities effectively
Keywords for Your Resume
Data ScientistData Science and Analyticsclinical trial feasibilityfit-for-purpose analyticsstudy designstudy benchmarkingcountry and site selectioncompetitive landscapeMachine Learningquantitatively informed site listsstatistical methodologiesstatistical analysesKPIsExcelSQLRPythondata mining techniquesTableauPower BIGood Clinical Practices (GCPs)ICH GuidelinesAbbVie Standard Operating Procedures (SOPs)
Deal Breakers
Bachelor's degree in statistics, analytics, bioinformatics, data science or equivalent field, 2-3 years of data science and analytics-related experience, Intermediate proficiency with visualization tools like Tableau, Power BI or equivalent, Complete or Full / Career proficiency in Excel, SQL, R, Python and/or other statistical packages
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