Drillo.AI
Overview
We are seeking a highly motivated and hands-on Data Scientist to join our analytics team at IQVIA. This role requires a self-starter who can design, build, and implement machine learning models to support critical healthcare analytics initiatives. The ideal candidate will have experience working with large-scale healthcare datasets, particularly patient longitudinal and claims data, and strong proficiency in Python and R. Key Responsibilities
Design, develop, and deploy machine learning models to derive insights from healthcare data. Work with patient longitudinal and claims data (Symphony or IQVIA datasets preferred) to uncover trends and generate actionable intelligence. Perform data cleaning, preprocessing, and feature engineering to prepare datasets for modeling. Implement predictive and statistical models, ensuring scalability and accuracy. Collaborate closely with internal IQVIA teams to support ongoing analytics projects and provide additional hands-on expertise. Communicate findings clearly through reports, dashboards, and presentations to both technical and non-technical stakeholders. Required Skills & Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field. Strong hands-on experience with Python and R for data manipulation, statistical modeling, and machine learning. Proven expertise in building, running, and implementing machine learning models. Experience working with patient longitudinal data and claims data (Symphony or IQVIA datasets strongly preferred). Solid understanding of statistical techniques, predictive modeling, and healthcare data standards. Strong problem-solving skills, attention to detail, and ability to work independently in a fast-paced environment. Preferred Qualifications
Prior experience in the healthcare or life sciences industry. Familiarity with big data tools and cloud platforms (e.g., AWS, GCP, Azure). Strong communication and presentation skills to effectively share insights. Note: This is only for USC/GC/ GC EAD candidates only This role is for W2 candidates only. No C2C allowed
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We are seeking a highly motivated and hands-on Data Scientist to join our analytics team at IQVIA. This role requires a self-starter who can design, build, and implement machine learning models to support critical healthcare analytics initiatives. The ideal candidate will have experience working with large-scale healthcare datasets, particularly patient longitudinal and claims data, and strong proficiency in Python and R. Key Responsibilities
Design, develop, and deploy machine learning models to derive insights from healthcare data. Work with patient longitudinal and claims data (Symphony or IQVIA datasets preferred) to uncover trends and generate actionable intelligence. Perform data cleaning, preprocessing, and feature engineering to prepare datasets for modeling. Implement predictive and statistical models, ensuring scalability and accuracy. Collaborate closely with internal IQVIA teams to support ongoing analytics projects and provide additional hands-on expertise. Communicate findings clearly through reports, dashboards, and presentations to both technical and non-technical stakeholders. Required Skills & Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field. Strong hands-on experience with Python and R for data manipulation, statistical modeling, and machine learning. Proven expertise in building, running, and implementing machine learning models. Experience working with patient longitudinal data and claims data (Symphony or IQVIA datasets strongly preferred). Solid understanding of statistical techniques, predictive modeling, and healthcare data standards. Strong problem-solving skills, attention to detail, and ability to work independently in a fast-paced environment. Preferred Qualifications
Prior experience in the healthcare or life sciences industry. Familiarity with big data tools and cloud platforms (e.g., AWS, GCP, Azure). Strong communication and presentation skills to effectively share insights. Note: This is only for USC/GC/ GC EAD candidates only This role is for W2 candidates only. No C2C allowed
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