- Location: NJ, United States
- Type: Contract
- Job ID: 10497
- Work Setting: On-Site
- Posted: July 28, 2026
- Closing Date: August 30, 2027
- Tax Status: W2
Data Scientist – Measurement & Attribution
12-month Contract
Remote: Monthly travel to Princeton, NJ
Pay Rate: Starting at $70/hr
Requirements
12-month Contract
Remote: Monthly travel to Princeton, NJ
Pay Rate: Starting at $70/hr
Requirements
- Support US-based attribution modeling capabilities by applying data science techniques to examine marketing activities and estimate their growth.
- Develop and revise code supporting measurement and attribution analytics.
- Work on projects involving Media Mix Optimization, Marketing Mix Modeling (MMM), Analysis of Covariance (test and control), Cluster Analysis, and Attribution Modeling of disaggregate event-stream data.
- Manage data collection and modeling with vendors.
- Develop reports and processes to ensure data quality control.
- Promote innovation in analytics and implement and refine attribution models.
- Interpret and visualize model estimates and diagnostics.
- Champion continuous improvement and strategic evolution.
- Measure both digital and offline marketing activities, including attribution, MMM, and linear TV impact.
- Work with offline data, including Salesforce, TV, digital media, and CRM data.
- Apply statistical and data science techniques, including regression, hierarchical or mixed regression, and machine learning techniques.
- Utilize advanced modeling skills with Python and R.
- Work in cloud environments, especially Snowflake.
- Work with platforms such as Dataiku and Databricks.
- Understand marketing goals and how different media channels support these goals.
- Proficiency in SQL, Python, and/or R or another statistical programming language.
- Experience in measurement of both digital and offline marketing activities.
- Experience with attribution modeling, Media Mix Modeling (MMM), and linear TV impact measurement.
- Experience working with and measuring offline, TV, digital media, and CRM data.
- Knowledge of statistics and data science.
- Knowledge of regression, hierarchical or mixed regression, and machine learning techniques, including Naïve Bayes, Markov Chain, and Random Forest.
- Advanced modeling skills with Python and R.
- Cloud environment experience, especially Snowflake.
- Experience working with platforms such as Dataiku and Databricks.
- Preference for experience in the pharmaceutical or life sciences industry.