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# Data Scientist III

- **Company:** Eliassen Group
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $145,600.0 - $166,400.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Big Data, Cloud Computing, IBM ILOG CPLEX Optimization Studio (CPLEX), Information Engineering, Python (Programming Language), SQL Databases, Workflow Management Systems, Snowflake, Apache Spark, AWS Glue
- **Published:** September 4, 2026
- **Apply:** https://www.dice.com/job-detail/8b8ea760-e31e-4548-80e2-ecccfe3fab32

## About the Role

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., * 5 to 10 years of experience in data science with strong time series forecasting background.

 * Proficiency in Python and SQL.
 * Experience working in cloud-based environments
 * Strong mathematical and statistical foundation with ability to explain methods and findings.
 * Experience with large-scale datasets, Spark, and orchestration tools such as Airflow.
 * Nice to have: data engineering experience and optimization exposure, including mixed-integer optimization using tools such as CPLEX or Gurobi.

## Description

Our client seeks a Data Scientist III focused on time series forecasting to support advertising viewership and inventory management. The role will investigate incoming first-party data and integrate it into existing forecasting models or develop new models as needed. The team operates in AWS with production workloads in SageMaker and related services. Collaboration with data engineers and reporting teams is expected, with clear communication of methods and results., * Investigate and assess new first-party data sources for relevance to forecasting objectives.

 * Integrate new data into existing time series forecasting models or develop new models when required.
 * Forecast linear and digital viewership to inform inventory planning and booking decisions.
 * Map projected audiences to available advertising inventory to support campaign commitments and SLAs.
 * Collaborate with data engineers to operationalize models using pipelines, workflows, and production processes.
 * Develop, document, and communicate modeling approaches, assumptions, and results to technical and non-technical stakeholders.
 * Work within an AWS-centric environment leveraging Python, SQL, Snowflake, SageMaker, Spark, Airflow, and AWS Glue.
 * Partner with upstream data provider teams to consume cleansed and prepared data.


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