Senior Manager, Go-to-Market Data Science

UCB•Atlanta, GA
•$125,600 - $180,600•Hybrid

About The Position

The Senior Manager, Go-to-Market Data Science is part of UCB’s Global Advanced Analytics team. The role uses secondary data and advanced analytics to develop business-impacting insights, increase the use of data, and, where appropriate, reduce the need to build primary data. It manages and implements advanced analytics and AI projects, oversees the ongoing operation and scaling of analytics solutions, and serves as a subject matter expert on advanced analytics and AI capabilities in support of business needs. The role partners with Global Advanced Analytics Team Leads, US and Global Go-to-Market Teams, Integrated Insights Hub Leads, and Patient Value Unit stakeholders. External partners include payors and analytics vendors. Its mission is to deliver actionable, data-driven insights that create high-impact patient value. The position is hybrid and based in the Atlanta, Raleigh, or Boston office, with 40% onsite presence.

Requirements

  • Bachelor’s degree in a quantitative area.
  • At least 6–8 years of experience applying predictive modeling techniques such as machine learning, decision trees, ensemble learning, and neural networks, and performing data transformations such as cleansing, integration, and fuzzy matching.
  • At least 6–8 years of experience developing program or project plans and leading programs or projects from initiation through implementation.
  • At least 6–8 years of programming and application development experience using Python or R.

Nice To Haves

  • Master’s or doctoral degree in a quantitative area.
  • Knowledge of the pharmaceutical industry, ideally specialty pharma and biologic treatments.
  • Deep expertise applying data science methodologies in the pharmaceutical Go-to-Market domain, including commercial, medical, and market access.
  • Expertise analyzing large secondary transactional databases, unstructured data, or other computationally difficult problems.
  • Mastery of project management skills.
  • Structured problem-solving ability.
  • An 80/20 mindset that supports fast model iterations.
  • Ability to interpret model results and identify potential model errors, such as overfitting, model bias, and confusion of correlation with causation.
  • Willingness and flexibility to work across geographies and time zones, sometimes outside core hours.

Responsibilities

  • Provide expertise on opportunities to leverage advanced analytics, particularly when it can reduce the need for primary data or deliver high marginal impact.
  • Deliver impactful data and analytics projects that address compelling business questions and identify opportunities for patients and UCB using effective displays of quantitative and qualitative information.
  • Partner strategically with Go-to-Market and functional stakeholders to co-create data and advanced analytics plans and priorities with Go-to-Market Hub Leads.
  • Collaborate closely with IT, the Data Office, and other Analytics teams using relevant data sources.
  • Mentor and guide junior data scientists and translators in applying advanced analytics, communicating and presenting insights, and implementing practical recommendations.
  • Drive execution of regional and local data-driven insights research and data analytics plans and priorities.
  • Foster a data science community across Hubs and Engines with strong business acumen and communication skills.
  • Supervise advanced analytics studies collaboratively and ensure study methodologies are appropriate for producing reliable results.
  • Develop and execute communication and collaboration plans with key UCB stakeholders to improve partnership and impact.
  • Build business knowledge within the Advanced Analytics team by ensuring team members interact directly with patients and/or other external stakeholders.
  • Attract, retain, motivate, coach, and develop talent on the Advanced Analytics team.
  • Build deep partnerships with Hub Insights teams, other Engines, and insight-generating functions, including regional analytics teams, to deliver cross-functional insights.
  • Champion a data-driven decision-making culture.
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