Advanced Analytics Associate Director - Kidney

Vertex Inc.•Boston, MA

2d•$157,800 - $236,600•Hybrid

About The Position

The Director of Kidney Analytics will provide advanced analytics and data science leadership for strategic commercial initiatives across the U.S. Kidney therapeutic area. This role will use sophisticated analytical, statistical, and data science methods to identify and quantify market drivers, barriers, risks, and opportunities. The Associate Director will lead the development of scalable data products, analytical models, dashboards, and reporting solutions that enable data-driven decision-making across the Kidney business. The ideal candidate combines deep commercial analytics expertise with strong technical and data science capabilities. They will be able to work with large, complex datasets; develop fit-for-purpose models; communicate technical findings clearly; and translate analyses into practical recommendations for senior stakeholders and cross-functional partners.

Requirements

Advanced Microsoft Excel modeling and data analysis.
SQL for data querying, transformation, and analysis.
Python for data manipulation, statistical analysis, predictive modeling, machine learning, and automation.
SAS and/or other statistical programming languages.
VBA.
Power BI dashboard design, development, data modeling, and maintenance.
Advanced statistical analysis, including regression, hypothesis testing, time-series analysis, and multivariate analysis.
Predictive analytics and machine-learning techniques, such as classification, clustering, segmentation, and model validation.
Data wrangling, data integration, feature engineering, and data-quality assessment.
Data visualization and executive-level analytical storytelling.
Analysis of large, complex pharmaceutical commercial and healthcare data sets.
Experience using pharmaceutical data sources, including: IQVIA or comparable third-party data-vendor data, Patient claims and longitudinal patient data, Prescription, distribution, and sales data, Internal sales, marketing, and CRM/field-call data
Microsoft PowerPoint for executive-ready reporting and communication.
Master’s degree in Data Science, Statistics, Biostatistics, Economics, Engineering, Computer Science, Finance, Science, or another quantitative discipline; equivalent relevant experience may be considered.
7–10 years of experience in biotechnology or pharmaceuticals in a quantitative role within Commercial, Analytics, Data Science, Finance, Corporate Strategy, or Business Development; or at least 4 years of relevant post-MBA or PhD experience in management, strategic, economic, analytics, or data science consulting with meaningful biotechnology/pharmaceutical decision-support experience.
Demonstrated experience developing and applying advanced analytics, statistical models, predictive models, or machine-learning approaches to complex commercial business questions.
Experience working with large, complex, and disparate healthcare, patient, commercial, sales, and marketing datasets.
Experience translating data science and analytical outputs into clear business insights, recommendations, and executive-level communications.
Experience building and maintaining KPI reporting, dashboards, performance analytics, and self-service business intelligence tools.
Strong knowledge of data quality, validation, documentation, metric definition, and analytical governance practices.
Proven ability to structure ambiguous problems, identify appropriate analytical methodologies, and synthesize findings from multiple data sources.
Experience partnering with senior leadership and cross-functional stakeholders in a matrixed biotechnology or pharmaceutical environment.
High degree of accuracy, attention to detail, intellectual curiosity, and accountability in the development of analyses and deliverables.
Ability to independently manage multiple priorities while building strong, collaborative relationships with colleagues and partners.

Nice To Haves

Experience supporting kidney disease, nephrology, rare disease, or specialty-care commercial businesses.
Experience developing commercial data science solutions in the pharmaceutical or biotechnology industry.
Experience with cloud-based data platforms, data warehouses, or analytical environments.
Familiarity with data engineering concepts, including ETL/ELT processes, data pipelines, data models, and automation.
Experience with real-world data, patient journey analysis, treatment pathway analysis, provider segmentation, and market access analytics.
Experience supporting product launch, pre-launch planning, in-line commercial strategy, market sizing, or opportunity assessment.
Familiarity with commercial sales operations, market access analytics, marketing analytics, and financial planning.
Experience establishing scalable reporting, data products, and analytical processes in an evolving therapeutic area.
Ability to balance analytical rigor, model interpretability, and practical business application.

Responsibilities

Partner with Forecasting and U.S. Kidney therapeutic-area stakeholders to identify strategic business questions, performance gaps, and opportunities for advanced analytics and data science solutions.
Define analytical requirements, recommend appropriate methodologies, and develop workplans that deliver timely, actionable insights.
Design, develop, validate, and maintain advanced analytics and data science models to identify and quantify market drivers, barriers, opportunities, risks, and emerging trends.
Apply statistical modeling, predictive analytics, machine learning, segmentation, classification, clustering, and other analytical techniques to address commercial business questions.
Develop models and analytical tools to evaluate patient, healthcare-provider, payer, market access, sales, and marketing dynamics relevant to the U.S. Kidney business.
Integrate data across internal and external sources to create scalable datasets, analytical assets, and business-ready insights.
Lead end-to-end KPI tracking, reporting, and performance analytics at national, regional, and territory levels.
Analyze business performance trends, identify root causes of performance changes, and provide evidence-based recommendations to support commercial decisions.
Develop scenario analyses, opportunity assessments, and other decision-support tools to evaluate potential commercial actions and risks.
Partner with IT, data engineering, and business stakeholders to define data requirements, improve data quality, and develop scalable reporting and analytics solutions.
Create, enhance, and maintain Power BI dashboards, self-service reporting tools, and automated reporting processes.
Establish clear metric definitions, data-validation practices, analytical documentation, and governance standards for recurring reporting and analytical products.
Develop executive-ready PowerPoint presentations, dashboards, reports, and visualizations that communicate complex analyses in a clear, concise, and compelling way.
Respond to ad hoc analytical questions by clarifying business needs, selecting appropriate data sources and methods, and delivering accurate, well-documented outputs.
Collaborate with U.S. Marketing, Global Marketing, U.S. Market Access, U.S. Finance, Commercial Sales Operations, IT, market research, and other analytical teams to develop an integrated understanding of Kidney business performance.
Communicate technical approaches, model outputs, assumptions, limitations, and business implications effectively to technical and non-technical audiences, including senior leadership.
Stay current on evolving data science, analytical, visualization, and commercial data capabilities and identify practical opportunities to improve analytical impact.