Decision Scientist

Eliassen Group; United States; Remote; USD 157,046,000 - 177,311,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401k with company matching

life insurance

Job summary

Eliassen Group is seeking a Decision Scientist to develop and operationalize forecasting, statistical, econometric, and machine learning solutions that support audience, viewership, advertising, and revenue management decisions.

The role includes building production-ready models and data pipelines, partnering with stakeholders to translate analytical needs into scalable solutions, and presenting findings to business leaders.

Qualifications

• Advanced expertise in statistics, forecasting, econometrics, and machine learning.
• Strong programming experience with Python and SQL.
• Experience with production data pipelines, cloud environments, CI/CD, Docker, and GitHub/GitLab.
• Expertise in time series forecasting, Bayesian statistics, generalized linear models, econometric modeling, machine learning algorithms, optimization, and simulation.
• PhD and experience in media/entertainment or audience/viewership analytics preferred.

Responsibilities

• Develop and maintain forecasting, statistical, econometric, and machine learning models.
• Analyze audience, viewership, advertising impressions, and demographic performance data.
• Support revenue management, pricing, and business decision-making initiatives across businesses.
• Build, deploy, and maintain production-ready data science solutions.
• Create and support automated data pipelines and model deployment processes.
• Partner with stakeholders to translate analytical needs into scalable solutions.
• Present findings and recommendations to business leaders and clients.

Skills

Python

SQL

Forecasting

Econometrics

Machine learning

Time series

Education

Master's or PhD in Statistics or related field

Tools

Docker

GitHub

GitLab

Snowflake

CI/CD

Relational databases

Job description

Description:

Remote

Our client seeks a Decision Scientist to develop and operationalize forecasting, statistical, econometric, and machine learning solutions that support audience, viewership, advertising, and revenue management decisions. The role includes building production-ready models and data pipelines, partnering with stakeholders to translate analytical needs into scalable solutions, and presenting findings to business leaders.

Due to client requirements, applicants must be willing and able to work on a w2 basis.

For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

• Medical
• Dental
• Vision
• 401k with company matching
• life insurance

Rate: $55.00 to $61.88/hr. w2

JN -092026-108667

Responsibilities:

• Develop and maintain forecasting, statistical, econometric, and machine learning models.
• Analyze audience, viewership, advertising impressions, and demographic performance data.
• Support revenue management, pricing, and business decision-making initiatives across businesses.
• Build, deploy, and maintain production-ready data science solutions.
• Create and support automated data pipelines and model deployment processes.
• Partner with stakeholders to translate analytical needs into scalable solutions.
• Present findings and recommendations to business leaders and clients.

Experience Requirements:

• Advanced expertise in statistics, forecasting, econometrics, and machine learning.
• Strong programming experience with Python and SQL.
• Experience with production data pipelines, cloud environments, CI/CD, Docker, GitHub and/or GitLab, and relational databases.
• Expertise in one or more of: time series forecasting, Bayesian statistics, generalized linear models, econometric modeling, machine learning algorithms, optimization, and simulation.
• Preferred: PhD, Snowflake, media or entertainment industry experience, audience or viewership forecasting, advertising and impressions analytics, revenue management and pricing analytics, linear TV or streaming analytics.

Education Requirements:

• Master's or PhD in Statistics, Econometrics, Operations Research, Industrial Engineering, Mathematics, Machine Learning, or a related quantitative field.