À propos
Remote
Commercial Pharma Causal Inference (would be a plus)
Mandatory Skills
Data Scientist with at least 5-7 yrs. of experience working in analytics and ML models that drove decision making.
The candidate must have core data science model based algorithms and insight generation using advanced analytics experience. Strong background in predictive modeling, classification, segmentation, and optimization Commercial Pharma Causal Inference (would be a plus) JD • Designing and implementing analytical frameworks. • Healthcare and commercial biopharma data sources such as claims data, HCP interaction logs, and prescription data. • Developing predictive and prescriptive models. • Lead the design and execution of advanced machine learning and causal inference models to measure and optimize omnichannel engagement strategies. • Experience applying causal inference techniques (e.g., causal impact analysis, uplift modeling, DoWhy) to marketing and engagement analytics. • 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. • Proficiency with programming languages like Python, R, and SQL. • Strong background in predictive modeling, classification, segmentation, and optimization. • Extensively worked in Azure Cloud environment.
Skill
Required Proficiency - On a scale of 1-5 (5 being the highest)
Keyword Search by TAG Team (in the profiles as first level screening)
Compétences linguistiques
- English
Avis aux utilisateurs
Cette offre provient d’une plateforme partenaire de TieTalent. Cliquez sur « Postuler maintenant » pour soumettre votre candidature directement sur leur site.