Website Aequor Technologies LLC
Aequor Technologies LLC
Company : Aequor Technologies LLC
The Data Scientist will work in the client group as part of the Data Science Team, and focus on a variety of Data Science projects across the board leveraging data from multiple internal R&D Systems and external Data Vendors enabling Data Driven culture across all R&D. The candidate will have direct accountability to build and productionize data science models and AI/ML tools allowing for proactive risk monitoring, pattern detection and predictive analytics. This is a very technical role, and we are looking for a candidate with strong technical acumen and passion for data science, who stays current on AI/ML development.
Job Responsibilities:
- Apply descriptive, predictive, and prescriptive analytics to inform business decisions throughout all stages of clinical study.
- Build advanced statistical models and machine learning tools to support Forecasting, Resource Allocation and Timeliness of clinical trial operational progress and milestones.
- Translate data analysis output into formalized messaging, insights and actions using PowerPoint and communicate effectively to stakeholders.
- Analyze trial related data to support external benchmarking studies, and extract insights from publicly available data sources to inform trial planning.
- Develop a centralized mechanism to analyze, alert & predict the site-, country-, study-, and portfolio-level risks & issues for ongoing and future clinical trial.
- Design the AI/gen-AI process to automate document review and implement chatbot functionality to facilitate data queries based on LLM framework.
Job Requirements:
- Minimum of 5 years' experience as a Data Scientist in Pharmaceutical Industry working with Clinical Trials Operational data / Real World Data.
- Minimum of 5 years' experience of coding in Python, R / R Shiny leveraging data science libraries
- Strong experience in building supervised and unsupervised machine learning methods and deploying them into production (i.e., regression models, random forests, decision trees, NLP, clustering etc.)
- Strong problem-solving skills
**Hybrid, 2 to 3 days a week onsite**