Data Analysis :
Manage and analyze pharmaceutical datasets (clinical trials, patents, research, market data) to identify promising drug candidates.Predictive Modeling :
Develop or collaborate with vendors to create machine learning models predicting the success and market potential of assets.Collaboration :
Work with scientists and executives to align data insights with pipeline strategy.Competitive Insights :
Monitor industry trends, identify gaps in therapeutic areas, and suggest partnership or acquisition opportunities.Data Sourcing & Cleaning :
Process and analyze data from various sources (FDA, EMA, PubMed, pharma databases).Visualization & Reporting :
Develop dashboards and reports to present findings clearly.Key Skills :
Technical :
Proficient in Python, R, SQL, and machine learning for predictive analytics and natural language processing (NLP).Pharma Tools :
Familiarity with pharma databases and cheminformatics tools (e.G., RDKit, Bioconductor).Data Visualization :
Skilled in tools like Tableau, Power BI, Matplotlib, Plotly.AI Expertise :
Knowledge in AI for drug development is a plus.Vendor Management :
Ability to oversee and manage vendors and suppliers.Strategic Insight :
Understanding of data science trends and their application in pharma.Domain Knowledge :
Therapeutics :
Knowledge of disease biology, drug mechanisms, and pharmacokinetics.Regulatory :
Familiarity with FDA / EMA approval processes and clinical trials.Business Acumen :
Understanding of pharma M&A trends and partnerships.Soft Skills :
Strong communication skills to translate technical findings to business strategy.Analytical thinking and problem-solving in uncertain data scenarios.Team-oriented and motivated to contribute in a biotech environment.Requirements :
Education :
Master’s / PhD in Data Science, Bioinformatics, Computational Biology, or similar.Experience :
3+ years in pharma / biotech analytics or drug development.Technical Proficiency :
Expertise in Python, R, SQL, and cheminformatics.Domain Knowledge :
Familiarity with clinical trials, regulatory processes, and therapeutic areas.Preferred Qualifications :
Experience with pharma datasets (e.G., IQVIA, Clarivate).Knowledge of emerging trends like AI-driven drug discovery.Familiarity with cloud platforms (AWS, Azure, GCP).Ongoing commitment to professional development.
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