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.