Hub Decision Science Manager

Job Purpose/Overview:

Responsible for driving analytics initiatives on behalf of the organization, including innovating, building, and maintaining well-managed data solutions and capabilities to solve business problems.  

Job Duties & Responsibilities:

• Demonstrated expertise in one pillar and a clear understanding and cross trained within a second pillar (Customer, Performance, Promotion, Relationship) with experience in how these pillars apply to Pharmaceutical Hub analytics
• Support 1-5 project work streams, creating a healthy environment for team collaboration and personal growth and client satisfaction
• Supports client-facing leads in the execution of project deliverables.
• Takes ownership of project timelines, from initial design through execution, ensuring timely project delivery, and collaborating effectively across functions to achieve successful project outcomes.
• Utilize creative, critical thinking and business conceptualization abilities to design and execute analytic projects
• Self-manage and/or lead decision support analysts in the design and execution of projects
• Anticipates needs and influences direction of client projects
• Able to set and manage ongoing client expectations on the process/goals effectively deliver projects
• Able to design workshops and facilitate segments of a workshop
• Anticipates unmet needs and proactively raises them to extend current project or initiate a new ones
• Execute targeting activities autonomously at the direction of senior members of Propensity4 including deciling/cohorting in line with Propensity4 approved methodologies
• Act as a key point of contact for internal stakeholders in our Pharmaceutical Hub analytics practice  

Leadership Responsibilities:

• Strong focus on supporting the health and wellbeing of the team
• Possesses a strong base of knowledge in Hub capabilities and Propensity4 methodologies and actively works to build a broader knowledge base within Propensity4
• Development and implementation of retention strategies to minimize attrition
• Building a supportive and caring team culture, recognizing success, and driving Engagement
• Responsible for supporting team member professional development
• Timely and consistent performance management
• Collaborates with peers to foster an inclusive, high performance culture

Technical Capabilities:

• Knowledge of different types of predictive models, including linear regressions, logistic regressions, experience in segmentations is a plus.
• Has a working knowledge of Pharmaceutical Hubs
• Solid base of understanding of payer coverage, benefit verification, prior authorizations, and co-pay programs.
• Insight into field reimbursement and patient support program analytics.
• Have experience with data integration and development of derived secondary and predictive metrics that are related to business questions 
• Demonstrated experience in producing clean dashboards and reports for operations, brand, or field teams.
• Proficient with advanced analytics tools and techniques such as SAS, SQL.  Experience with R and/or Python preferred.
• Proficient in business intelligence tools such as Tableau, Qlik, PowerBi, etc

Requirements & Qualifications:

• Master’s Degree in Statistics, Mathematics, Economics, Engineering, or other quantitative discipline is preferred.
• 5-8 years of experience in Pharmaceutical Analytics capabilities including payer analytics, pharma marketing analytics, commercial operations, or analytics consulting
• 2-5 years of direct experience with pharma hub programs, especially in roles tied to Patient access analytics, operational performance of patient support programs, or adherence and persistence modeling
• Must exhibit strong communication skills with resounding abilities in connecting data and analytic techniques to related business questions
• Required to have experience with data integration and development of derived secondary and predictive metrics that are related to business questions
• Strong in SAS, R, Python, and Excel. Experience with VBA is a plus
• Expertise with different types of predictive models, including linear regressions, logistic regressions, experience in segmentations is preferred
• Must be able to work with large datasets in different formats
• Must be able to analyze data and turn it into actionable business insights and strategies
• Must be a proactive and critical thinker who can take initiatives and reveal trends and patterns in data
• Ability to present findings to a non-technical audience
• Strong attention to detail and documentation
• Excellent oral and written communication skills
• Self-starter who can work in a fast-paced, entrepreneurial environment and ability to adapt to change.

Don't meet every job requirement? That's okay! Our company is dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role, but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.