Associate Director – US Market Engagement, HIV

• Translate business needs and priorities to build analytical plans that answer business questions by providing actionable insights.
• Effectively communicating advanced analytics to stakeholders to inform business decisions.
• Communicate & collaborate effectively with cross functional teams with competencies in market research, forecasting, commercial analytics, data science, customer engagement, data strategy, population health, competitive insights, marketing operations, medical & clinical backgrounds.
• Analyze data across disparate databases/sources (including claims, CDC, digital/CRM and other sources) to develop insights that inform commercial business strategies.
• Stay current with industry trends and advancements in analytical methodologies to bring new ideas forward (including application of AI/GenAI) that will enhance analytic capabilities of the organization especially as we are taking a AI forward thinking approach.
• Propose innovative ideas for analytical approaches and AI/ML/NLP/modeling techniques, demonstrating strong conceptual understanding of methods and trade-offs.
• Derive actionable business insights from various data sources, develop clear data story, and communicate effectively to business stakeholders.
• Lead and mentor a team of data scientists and business analysts (on-shore and off-shore), providing guidance on best practices in data analytics, modeling and data visualization, through the scope of a project.

• 5+ years of analytics or data science experience in pharma/biotech/healthcare; HIV experience preferred.
• Proven data science experience leveraging advanced statistical methods, Machine Learning/ Artificial Intelligence, Natural Language Processing (NLP) modeling and model evaluation is a plus.
• Proficiency in Python, R studio, SAS, SQL etc. or similar tools for data extraction, feature engineering, and model development.
• Strong experience with patient-level and healthcare data (claims, EMR/EHR, registry, CDC, IQVIA and other secondary sources).
• Understands the business context, challenge, limitation, constraints and goals to effectively match the capability of the statistical and mathematical and M/L approaches to the business, scientific and operational challenge
• Demonstrated ability to translate business needs into structured analytical questions and data-driven recommendations.
• Strong communication and data storytelling skills, including presenting complex findings to senior and non-technical audiences.
• Solid project and time management capabilities, with experience leading multiple concurrent analytics initiatives and teams.

Expertise in data analytics and data science within the pharma and healthcare sectors, with a strong focus on leveraging Machine Learning, AI, and NLP techniques to derive actionable insights. Proven ability to communicate complex data findings effectively to diverse stakeholders while leading and mentoring analytics teams.

• Data Science Experience
• Machine Learning
• Natural Language Processing
• Python Proficiency
• Healthcare Data Analysis

• Data Analytics
• Statistical Methods
• Model Development
• Feature Engineering
• Data Visualization
• Data Extraction
• Advanced Analytics
• Analytical Methodologies
• Data Storytelling
• Project Management

• Communication Skills
• Collaboration
• Mentoring
• Time Management
• Problem Solving

• Pharma
• Biotech
• Healthcare
• HIV Experience
• Patient-Level Data
• Claims Data
• EMR/EHR
• CDC
• IQVIA
• Commercial Analytics

• Python
• R Studio
• SAS
• SQL
• AI/GenAI