What are the responsibilities and job description for the Data Scientist position at Galent?
Job Details
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 Google Cloud Platform) is a plus.
Strong problem-solving skills, intellectual curiosity, and a proactive approach to driving impact through data science.
