Senior Analyst, Decision Sciences

Responsibilities

• Turn Data Into Strategy: Access, validate, analyze, and interpret complex datasets to solve critical marketing challenges, including promotional effectiveness, attribution, and marketing mix optimization.
• Build Analytics-Ready Foundations: Design clean, well-documented, and efficient data pipelines. Gather requirements, verify data integrity, and work closely with Data Governance to maintain the highest standards of data security and confidentiality.
• Develop Advanced Models: Build and maintain predictive and explanatory statistical models, uncovering underlying patterns, trends, and anomalies.
• Bridge Analytics and Business: Translate complex statistical outputs and modeling methodologies into compelling narratives, dashboards, and recommendations for both technical and non-technical stakeholders.
• Foster Innovation & Team Growth: Contribute to our analytical toolbox, explore emerging methodologies, and help mentor team members on statistical techniques and interpretation.

Requirements

• Proven Experience: 3–5 years of experience as an analyst focused on custom analytics, predictive modeling, or custom metric development.
• Educational Foundation: Bachelor’s degree in Statistics, Mathematics, Data Science, Economics, or a related quantitative field ( Master’s degree preferred ).
• Hands-on coding experience with statistical tools such as Python, R, SAS, or SPSS (collaborative coding and macro/function development experience is a plus).
• Strong data visualization expertise using Tableau or Microsoft Power BI .
• Advanced Excel skills (complex formulas, pivot tables, charting; VBA is a bonus).
• Core competencies in data transformation, regression analysis, correlation, cross-tabulation, ANOVA/ANCOVA, and survey design/analysis.
• Practical familiarity with advanced techniques: Marketing Mix Modeling (GLM), decision trees (CART/CHAID), cluster/discriminant analysis, time-series forecasting (ARIMA, exponential smoothing), or machine learning/text analytics.
• Strong Communication: The ability to explain complex quantitative concepts with clarity, precision, and confidence to cross-functional partners and external clients.
• Mindset: Highly curious, detail-oriented, self-directed, and committed to high integrity and data ethics.

Preferred

• Experience in the pharmaceutical / healthcare industry.
• Familiarity with healthcare data assets (e.g., IMS / IQVIA health data).

Benefits

• Work on high-visibility projects that directly influence client growth and strategic investment.
• Collaborative, continuous-learning culture with exposure to modern tools and advanced methodologies.
• Competitive compensation, comprehensive benefits package, and opportunities for career advancement.