Senior Analyst, Decision Sciences

CMI Media Group; United States; On-site; USD 50,000 - 90,000; Full time

Job summary

CMI Media Group seeks a Senior Analyst in Decision Sciences to power client strategies through rigorous analytics, marketing mix modeling, and ROI optimization. You will turn complex data into actionable insights and guidance for stakeholders.

Ideal candidates have 3–5 years of analytics experience, a quantitative degree, and strong skills in Python/R/SAS/SPSS, Tableau/Power BI, and advanced Excel. Healthcare data familiarity is a plus.

Qualifications

• 3–5 years of experience as an analyst focused on custom analytics, predictive modeling, or custom metric development.
• 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.
• 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.
• Familiarity with Marketing Mix Modeling (GLM), decision trees (CART/CHAID), cluster/discriminant analysis, time-series forecasting (ARIMA, exponential smoothing), or ML/text analytics.
• Strong communication to explain complex quantitative concepts to cross-functional partners and clients.

Responsibilities

• Turn Data Into Strategy: analyze complex datasets to measure promotional effectiveness, attribution, and marketing mix optimization.
• Build Analytics-Ready Foundations: design data pipelines, ensure data integrity, and support data governance for security and confidentiality.
• Develop Advanced Models: build predictive and explanatory models to reveal patterns and trends.
• Bridge Analytics and Business: translate outputs into dashboards and actionable recommendations for diverse stakeholders.
• Foster Innovation & Team Growth: contribute to analytical toolbox and mentor teammates on statistical techniques.

Skills

Statistical thinking

Data storytelling

Self-direction

Attention to detail

Collaborative mindset

Education

Bachelor’s degree in Statistics, Mathematics, Data Science, Economics, or related field

Master’s degree preferred

Tools

Python

R

SAS

SPSS

Tableau

Power BI

Advanced Excel

Job description

Make Data-Driven Marketing Impactful

Are you passionate about unlocking the stories hidden within complex data? Do you thrive on turning sophisticated statistical modeling into clear, actionable marketing strategies?

We are looking for a Senior Analyst, Decision Sciences to join our team. In this role, you will be the analytical engine powering strategic decisions for our clients—measuring promotional channel effectiveness, calculating marketing ROI, and optimizing marketing mix strategies. If you combine strong statistical rigor with the communication skills to translate quantitative insights into real-world business impact, we want to hear from you.

What You’ll Do

• 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.

What You Bring

• 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).
• Technical & Programming Toolkit:
  • 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).
• Solid Statistical Foundation:
  • 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.

Bonus Points If You Have

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

Why Join Us?

• 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.

The base salary for this position at the time of this posting may range from $50,000 to $90,000. Individual compensation varies based on job related factors, including business needs, experience, level of responsibility and qualifications.