Analyst, Data Science

Job summary

Develop and deliver quantitative models and statistical analyses for marketing clients, focusing on predictive modeling and regression. Responsibilities include building Marketing Mix Models, performing data validation, and preparing structured outputs for client review.

Job details

Agency Omnicom Media Job Function Data and Analytics Job Subfunction Data Science and AI Job Description Position Summary We are looking for a Data Science Analyst to join our growing data science practice. In this role, you will support the development and delivery of quantitative models and analyses across a portfolio of marketing clients, including predictive modeling, regression analysis, and statistical work spanning media, pricing, and promotional data. This is a great entry point for someone with a strong statistics background who wants to apply analytical skills in a fast-paced, client-service environment. Key Responsibilities Build and maintain data science models such as Marketing Mix Models using regression-based techniques, working with weekly or monthly time-series data across media, pricing, and promotional variables. Conduct data validation, cleaning, and QA on client-provided datasets to ensure model-ready inputs. Run statistical analyses including adstock transformations, diminishing returns curves, and decomposition outputs. Support model documentation and prepare structured outputs (Excel workbooks, charts, summary tables) for internal and client review. Collaborate with senior team members on methodology decisions and model refinement. Contribute to internal tooling and process improvements as the team scales. Desired Skills & Experience Bachelor's or Master's degree in Statistics, Mathematics, Economics, Data Science, or a related quantitative field. Strong foundation in statistical modeling, particularly regression analysis and time-series methods. Comfort working in Python or R for data manipulation, modeling, and visualization (pandas, statsmodels, scikit-learn, or equivalent). Familiarity with concepts such as multicollinearity, heteroscedasticity, model fit diagnostics, and variable selection. Attention to detail and the ability to work carefully through large, messy datasets. Clear written communication skills for documenting analytical work. Exposure to Bayesian methods or hierarchical modeling. Experience with marketing data (media spend, impressions, GRPs) or consumer datasets. Prior internship or academic project experience in an applied analytics setting. Salary Range: $55,000 - $65,000 Omnicom’s policy requires employees to work in the office for a minimum of three days a week, unless additional in-office days are directed by their agency or manager. Our objective is to increase this requirement over time, and many of our agencies as well as Omnicom’s corporate group already require five days of in-office attendance. Omnicom is committed to hiring and developing exceptional talent. We agree that talent is uniquely distributed, and we’re focused on developing inclusive teams that can bring the best solutions to everything we do. We strongly believe that celebrating what makes us different makes us better together. Join us—we look forward to getting to know you. We will process your personal data in accordance with our Recruitment Privacy Notice. Link to Recruitment Privacy Notice: https://www.omc.com/privacy-notice/ , Salary Range: $55,000 - $65,000

What you’ll do

Develop and deliver quantitative models and statistical analyses for marketing clients, focusing on predictive modeling and regression. Responsibilities include building Marketing Mix Models, performing data validation, and preparing structured outputs for client review.

Requirements

Requires a degree in a quantitative field like Statistics or Data Science with a strong foundation in regression and time-series methods. Proficiency in Python or R and familiarity with statistical diagnostics and marketing data are desired.

Listed skills

• Data visualization · Preferred
• Data Validation · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Predictive Modeling
• Regression Analysis
• Statistical Modeling
• Python
• R
• Time-Series Analysis
• Data Validation
• Data Cleaning
• Marketing Mix Modeling
• Pandas
• Statsmodels
• Scikit-learn
• Bayesian Methods
• Hierarchical Modeling
• Data Visualization

Job areas

• Data & Analytics
• Marketing
• Science & Research
• Consulting
• Creative & Media