Data Scientist

Veridic Solutions; Charlotte (NC); On-site; USD 110,000 - 170,000; Full time

Job summary

Veridic Solutions is seeking a data scientist to build and maintain forecasting models that align ad inventory with viewer profiles. You will forecast capacity, work with first- and third-party data, and integrate newly merged first-party data into models.

The role requires practical data science experience, independence in solving modeling problems, and comfort with CI/CD processes. Cloud-based environment, Snowflake, Python, and SQL are central to daily work.

Qualifications

• Solid, practical data science experience; not an absolute expert.
• Ability to work independently on modeling problems.
• Experience in a team with CI/CD exposure.
• Comfort with data engineering tasks to support modeling.
• Candidates from a Finance background are not a strong fit.
• Proficiency in Python and SQL.
• Experience with time series forecasting.
• Snowflake data warehouse experience.
• AWS cloud-based environment.
• Nice to have: SageMaker, Airflow, PySpark.

Responsibilities

• Build and maintain models that align advertising inventory with subscriber viewing profiles.
• Forecast advertising capacity, including sold vs. unsold airtime and inventory.
• Work with first-party and third-party data sources.
• Incorporate newly integrated first-party data into forecasting models.
• Collaborate with a cross-functional team following CI/CD practices.
• Take on light data engineering tasks to support modeling.

Skills

Time series forecasting

Data science experience

Tools

Python

SQL

Snowflake

AWS

SageMaker

Airflow

PySpark

Job description

• Build and maintain models that align advertising inventory with subscriber viewing profiles
• Forecast advertising capacity, including sold vs. unsold airtime and acquired vs. owned (Spectrum) inventory
• Work with both first-party (Charter, and now Cox) and third-party data sources
• Incorporate newly integrated first-party data (from the Cox merger) into existing forecasting models
• Collaborate with a cross-functional team, following established CI/CD practices
• Take on light data engineering tasks as needed to support modeling work
• What We're Looking For
• Solid, practical data science experience — this is not a role requiring deep specialization or "absolute expert" level skills
• Someone who understands what they're doing and can work independently on modeling problems
• Experience working as part of a team, ideally with exposure to CI/CD processes
• Comfort doing some data engineering work in support of modeling (not a pure modeling-only candidate)
• Candidates from a Finance background are not a strong fit for this role
• Languages/Tools: Python, SQL
• Time series & Forecasting Experience
• Data Warehouse: Snowflake (corporate data warehouse)
• Cloud: AWS (fully cloud-based — no on-prem infrastructure)
• Nice to Have: SageMaker, Airflow, PySpark