Associate Director, Marketing Sciences

Role Summary

Associate Director, Marketing Sciences will proactively bring innovative data science techniques and insights to the business to drive and support strategic decisions. This role is responsible for standing up the capability of integrated HCP, patient journey and predictive sciences at scale for the commercial market. The position reports to the Sr. Director, Marketing Sciences and is office-based/hybrid in Foster City, CA or Parsippany, NJ.

• Be a partner in driving the industrialization of predictive sciences to help understand the patient journey and triggers robustly for markets.
• Understand commercial business objectives, develop and deploy scalable data science products and insights to influence decisions in marketing, sales, medical, and related areas.
• Lead data science projects end to end, convert unstructured business questions into data science solutions, guide offshore teams, be a hands-on leader who can code and debug, and communicate with stakeholders.
• Foster a culture of measurement and impact, and incorporate feedback to continuously improve data science models.
• Bring thought leadership and thorough understanding of statistics and predictive methodologies to construct robust propensity models for commercial use.
• Create data science products that can be refreshed, reproduced, and replicated.
• Work with other data scientists and analysts to define retraining schedules and measure propensity models for impact.
• Partner with global teams to cross-pollinate ideas and replicate successful models across regions.
• Demonstrate excellent communication and the ability to abstract backend complexity where not needed.

• Basic Qualifications: Bachelor's Degree and Ten Years' Experience, Master's Degree and Eight Years' Experience or PhD and Five Years' Experience; strong working knowledge of machine learning algorithms (regression, clustering, neural networks, Bayesian models, RNN, CNN, tree-based algorithms such as RF, XGBoost, Light
  
  GBM, SMOTE, etc.); experience in building, implementing and using AI-based solutions with proven business impact; strong leadership to manage initiatives end-to-end; effective written and verbal communication skills.
• Preferred Experience: Experience implementing and optimizing AI-based solutions with proven business impact; experience with standard pharma and consumer data types/sources (patient claims, Xponent, Plantrak, sales, activity); expertise with pharma datasets (IQVIA, Symphony, Komodo claims, Optum, Definitive Health, Health Verity, EMR/HER); proficiency in Python and data science libraries (numpy, pandas, scikit-learn, seaborn, networkx); knowledge of ANCOVA, Bayesian statistics, econometric modeling, neural networks/logistic regression;
  
  familiarity with cloud technologies (Databricks, S3); demonstrated product mindset and familiarity with product management principles; strong teamwork, inclusivity, and cross-functional collaboration; understanding of emerging data science capabilities in pharma/healthcare; thorough understanding of datasets and their limitations; advanced degree in a quantitative field with substantial relevant experience OR substantial relevant experience with a related undergraduate degree.