What are the responsibilities and job description for the Data Scientist position at Galent?
Sr Data Scientist
Raleigh, NC (Onsite)
- JOB RESPONSIBILITIES
- Lead the design and execution of advanced machine learning and causal inference models to measure and optimize omnichannel engagement strategies.
- Exercise independent judgment in methods, techniques, and evaluation criteria on data science projects, overseeing the end-to-end process from problem definition to model implementation.
- Work with large-scale healthcare datasets, including claims data, prescription data, digital engagement logs, and survey data, to derive insights on HCP behavior.
- Partner with commercial, marketing, and business development teams to translate data insights into strategic recommendations that enhance customer engagement.
- Act as a key data science representative in client engagements, effectively communicating insights, methodologies, and recommendations to both technical and non-technical stakeholders.
- Have broad analytics experience or innovative knowledge and use skills to contribute to achieving client objectives in creative and effective ways.
- Foster innovation by exploring and integrating emerging technologies and methodologies.
QUALIFICATION REQUIREMENTS
- Master’s degree or equivalent experience in Data Science, Computer Science, Mathematics, Statistics, or a related field. PhD is preferred.
- Proficiency with programming languages like Python, R, and SQL.
- Experience applying causal inference techniques (e.g., causal impact analysis, uplift modeling, DoWhy) to marketing and engagement analytics.
- Strong background in predictive modeling, classification, segmentation, and optimization.
- Familiarity with healthcare and commercial biopharma data sources such as claims data, HCP interaction logs, and prescription data.
- Experience engaging with clients and strong ability to bridge the gap between technical and business audiences.
- Ability to translate complex data science concepts into strategic business insights for non-technical stakeholders.
- Experience deploying models in cloud-based environments (AWS, Azure, or GCP) is a plus.
- Strong problem-solving skills, intellectual curiosity, and a proactive approach to driving impact through data science.
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