Data Scientist

GForce Life Sciences; Princeton (NJ); Hybrid; USD 120,000 - 180,000; Full time

Job summary

GForce Life Sciences is seeking a Data Scientist for Measurement & Attribution on a 12-month contract. The role combines data science with marketing analytics, focusing on attribution modeling, MMM, and analysis of disaggregate event-stream data, with monthly travel to Princeton, NJ.

You will work with Python, R, SQL, and platforms like Dataiku, Databricks, and Snowflake to build models, manage data with vendors, and deliver reports that drive marketing decisions.

Qualifications

• 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, 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.

Responsibilities

• Support US-based attribution modeling capabilities by applying data science techniques.
• Develop and revise code supporting measurement and attribution analytics.
• Work on MMM, analysis of covariance, 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 attribution models.
• Interpret and visualize model estimates and diagnostics.
• Measure digital and offline marketing activities including TV impact.
• Work with offline data including Salesforce, TV, digital media, and CRM data.

Skills

SQL

Python

R

Attribution modeling

Media Mix Modeling

MMM

Statistics

Regression

Machine learning

Data visualization

Snowflake

Dataiku

Databricks

Naïve Bayes

Markov Chain

Random Forest

Tools

Dataiku

Databricks

Snowflake

Job description

Data Scientist – Measurement & Attribution

12-month Contract

Remote: Monthly travel to Princeton, NJ

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.

Qualifications

• 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.