Senior Manager, Digital Centric Commercialization (DCC) Analytics and Opera at Axsome Therapeutics

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

05 May, 26

Salary

160000.0

Posted On

04 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Optimization Algorithms, Commercial Analytics, SQL, Python, R, Data Analysis, Modeling, Excel, Pharmaceutical Data, HCP Segmentation, Targeting, Resource Allocation, Communication Skills, Promotional Response Patterns

Industry

Biotechnology Research

Description

Axsome Therapeutics is a biopharmaceutical company leading a new era in the treatment of central nervous system (CNS) conditions. We deliver scientific breakthroughs by identifying critical gaps in care and develop differentiated products with a focus on novel mechanisms of action that enable meaningful advancements in patient outcomes. Our industry-leading neuroscience portfolio includes FDA-approved treatments for major depressive disorder, excessive daytime sleepiness associated with narcolepsy and obstructive sleep apnea, and migraine, and multiple late-stage development programs addressing a broad range of serious neurological and psychiatric conditions that impact over 150 million people in the United States. Together, we are on a mission to solve some of the brain’s biggest problems so patients and their loved ones can flourish. For more information, please visit us at www.axsome.com and follow us on LinkedIn and X. About This Role Axsome Therapeutics is seeking a Senior Manager, Digital Centric Commercialization (DCC) Analytics and Operations to lead the evolution of our Next Best Action capabilities and manage exponentially increased complexity from our multi-brand, multi-team commercial portfolio. This highly technical role requires expertise in machine learning, optimization algorithms, and commercial analytics to transition DCC Intelligence from static, single-model suggestions to a continuous test-and-learn framework. The position is critical for implementing multi-team optimization that allocates promotional activities across overlapping sales forces to maximize profitability while avoiding customer fatigue. This role is based at Axsome’s HQ in New York City with an on-site requirement of at least three days per week. We are unable to consider candidates who are looking for fully remote roles. Job Responsibilities and Duties include, but are not limited to, the following: Build linear optimization engine that allocates promotional calls across multiple teams to overlapping HCP targets. Develop objective functions maximizing expected revenue while incorporating constraints including call capacity, contact limits, customer fatigue thresholds, and strategic imperatives; responsible for managing this process on a quarterly basis Design and implement continuous test-and-learn framework for Next Best Action (NBA) suggestions that include business rules, ML models, and hybrid approaches Design comprehensive DCC performance dashboard with leading and lagging indicators Develop suite of advanced predictive models including HCP propensity to prescribe, churn risk etc. Create ad hoc analyses to identify field execution opportunities and commercial optimization insights based on CRM engagement data, promotional response patterns, and secondary data sources (IQVIA/Symphony) Support Sales leadership in the organization and coordination of National Sales Meetings, Manager Meetings, and Period-of-Action (POA) planning sessions Requirements / Qualifications BS/MS/PhD in Engineering, Physics, Applied Physics, Statistics, Computer Science, or related quantitative field strongly preferred 6 years of sales operations experience in the pharmaceutical or biotech industry (which may include work as a consultant or supplier to the industry) Expert-level SQL skills for complex queries, joins, and data manipulation. Advanced proficiency in Python (pandas, numpy) or R for data analysis and modeling Advanced Excel capabilities including VBA/macros, Power Query, Power Pivot, and complex formula design Experience, Knowledge and Skills Strong understanding of key pharmaceutical data sources (IQVIA, Symphony, claims data) and data structures to produce actionable insights Excellent written and verbal communication skills with ability to translate complex technical concepts into clear business insights for all organizational levels Experience in hcp segmentation, targeting and resource allocation. Salary & Benefits The anticipated salary range for this role is $140,000 - $160,000. We encourage candidates of all levels to apply as there may be flexibility on final job title and responsibilities. The salary offer will be based on a variety of factors, including experience, qualifications, internal equity and location. Axsome offers a competitive employment package that includes an annual bonus, significant equity and a generous benefits package. Axsome is committed to equal employment opportunity and providing reasonable accommodations to applicants with physical and/or mental disabilities. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, gender, sex, age, religion, creed, national origin, sexual orientation, gender identity, ancestry, citizenship, marital status, physical or mental disability, medical condition, veteran status, genetic information, or any other characteristic protected by federal, state, or local law. Axsome Therapeutics does not accept unsolicited resumes from recruiters or third-party recruitment agencies and will not pay placement fees for unsolicited candidates that are sent to hiring managers, the HR team or other Axsome team members. Only approved vendors who have been explicitly asked to support a specific search will receive access to our Applicant Tracking System to submit candidates for consideration.

Responsibilities

Lead the evolution of Next Best Action capabilities and manage complexity from a multi-brand commercial portfolio. Build optimization engines and develop predictive models to maximize profitability and improve commercial insights.