Associate Director, Marketing Sciences

Gilead Sciences • Foster City, CA

12d • Hybrid

About The Position

At Gilead our pursuit of a healthier world for all people has yielded a cure for hepatitis C, revolutionary improvements in HIV treatment and prevention as well as advancements in therapies for viral and inflammatory diseases and certain cancers. We set and achieve bold ambitions in our fight against the world’s most devastating diseases, united in our commitment to confronting the largest public health challenges of our day and improving the lives of patients for generations to come. . As an Associate Director, Data Science, you will proactively bring innovative data science techniques and insights to business to drive/support strategic business decisions. You would be responsible for standing up the capability of integrated HCP, patient journey and predictive sciences at scale for commercial market. The person will work closely with integrated insights, commercial ops, patient engagement and omni channel analytics leads. Hands on functional expertise, highly collaborative mindset and leadership skillsets required. This role will report to Sr. Director, Marketing Sciences and is office based/hybrid located in either Foster City, CA or Parsippany, NJ.

Requirements

• Bachelor's Degree and Ten Years' Experience, Masters' Degree and Eight Years' Experience or PhD and Five Years' Experience
• Strong working knowledge of machine learning algorithms, including regression, clustering, neural networks, Bayesian models, RNN, CNN, Tree-based algorithms (RF, XGB, LightGBM), SMOTE and etc.
• Experience in building, implementing and using AI-based solutions with proven business impact
• Strong leadership that be able to manage initiatives from beginning to end himself/herself
• Effective written and verbal communication skills

Nice To Haves

• Experience in implementing, optimizing and using AI-based solutions to establish proven business impact
• Experience working with standard pharma and consumer data types and sources such as patient claims, Xponent, Plantrak, sales, activity.
• Expertise in commonly used pharma datasets such as IQVIA, Symphony, Komodo claims, Optum, Definitive health, Health Verity, EMR/HER
• Expertise in Python including commonly used data science libraries such as numpy, pandas, scikit-learn, seaborn, networkx, etc.
• Expertise in data science techniques such ANCOVA, Bayesian Statistics, Econometric modeling, Neural Networks/Logistic, etc.
• Understanding of cloud-based technologies and tools such as Databricks, S3, etc.
• Demonstrated product mindset
• Familiarity with product management principles
• Effective written and verbal communication skills
• Strong team player. Inclusive, objective, cross-functional, team member with a positive and solution-oriented mindset
• Understanding of emerging data science capabilities (fields, methodologies, algorithms, etc.) and potential application in pharma/health care
• Thorough understanding of datasets including their strengths and limitations such as capture rate, projections and acceptable error ranges for different therapeutic spaces
• Masters degree in a quantitative field with at least 8 years of relevant data science/analytics experience OR Undergraduate degree in a quantitative field with at least 10 years of relevant data science/analytics experience

Responsibilities

• Be a partner in driving the industrialization of predictive sciences to help understand the patient journey and triggers robustly for markets.
• Understand Gilead's commercial business objectives, develop and deploy scalable data science products and insights to influence decisions in marketing, sales, medical and etc.
• Lead Data science projects end to end include convert unconstructured business questions into data science solutions, give guidance to offshore, be a hands-on leader who knows how to code and debug, communicate with stakeholders and etc.
• Foster a culture of measurement and impact and incorporate feedback to continuously improve data science models
• Bring thought leadership and thorough understanding of statistics, primarily predictive algorithms & methodologies, to construct robust propensity models for impactful commercial use
• Create data science products that can be refreshed, reproduced and replicated
• Work with other Data Scientists and Analysts to define retraining schedule and measure propensity models for impact
• Partner with global teams to cross-pollinate ideas and replicate successful models from other countries and vice versa
• Excellent communication and ability to abstract backend complexity where it is not needed

Benefits

• This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package.
• Benefits include company-sponsored medical, dental, vision, and life insurance plans.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees