Sr. Data Scientist

Delan Associates, Inc; Charlotte (NC); On-site; USD 110,000 - 150,000; Full time

Job summary

Delan Associates, Inc. is seeking a Data Scientist to join a cloud-based team focused on advertising inventory modeling and capacity forecasting for a large subscriber base.

You will build models that align inventory with viewing profiles and forecast capacity across sold/unsold airtime and acquired/owned inventory. The role involves working with first- and third-party sources (including Cox data) and applying CI/CD practices within a fully cloud-based setup using Python, SQL, Snowflake, and

Qualifications

• Practical data science experience with applied modeling.
• Ability to work independently on modeling problems.
• Experience in a team environment and CI/CD workflows.
• Data engineering exposure to support modeling efforts.

Responsibilities

• Build and maintain models that align advertising inventory with subscriber profiles.
• Forecast advertising capacity including sold vs. unsold airtime.
• Integrate first- and third-party data sources (including Cox data).
• Collaborate with cross-functional teams and apply CI/CD practices.
• Perform light data engineering tasks to support modeling.

Tools

Python

SQL

Snowflake

AWS

SageMaker

Airflow

PySpark

Job description

Job Description:

Interviews: Live, Technical Hands On

About the Role

We’re looking for a Data Scientist to join a team focused on advertising inventory modeling and capacity forecasting for client’s subscriber base. This team builds models that match commercials and ads to subscriber profiles based on viewing behavior, identifies gaps in that targeting, and works to fill them through marketing data. A core part of the role is forecasting available advertising capacity — balancing sold vs. unsold airtime, and understanding the difference between acquired inventory and Spectrum’s own inventory, as well as true demand vs. true capacity.

The team works with a blend of client’s proprietary subscriber data and third-party data sources. Notably, data from Cox — previously treated as third-party — became first-party data as of a recent company merger, and this shift is actively being incorporated into forecasting models.

This is a great opportunity for a data scientist who enjoys applied modeling work with real business impact, in a fully cloud-based environment.

What You’ll Do

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

Tech Stack

Languages/Tools: Python, SQL

Time series & Forecasting Experience

Data Warehouse: Snowflake (corporate data warehouse)

Cloud: AWS (fully cloud-based — no on-prem infrastructure)

ML Tooling: Various data science libraries

Nice to Have: SageMaker, Airflow, PySpark