Data Scientist 3 - Comcast Advertising

Comcast Advertising is driving the TV advertising industry forward, from delivering ads to linear and digital audiences to pioneering the tech that makes it possible. We help brands connect with their audiences on every screen using advanced data, technology, and premium video content. Our media sales division helps local, regional, and national brands reach potential customers through multiscreen TV advertising. Our ad tech division FreeWheel provides comprehensive adtech that makes it easier to buy and sell premium video advertising across all screens, data types, and sales channels.

Job Summary

This job involves extracting insights from complex, high-dimensional data using advanced data science techniques. It requires developing predictive models and analytical solutions to boost business performance. The role is key for driving data-informed business strategies and decisions.

Job Description

• Responsibilities:

• Collaborating with cross-functional teams to define data-driven questions and conduct experiments for product and service enhancements
• Engineering and refining algorithms, software, and automated processes for robust data integration and cleansing from multiple sources
• Utilizing statistical rigor and advanced data science methods to analyze large datasets, deriving insights through predictive models and machine learning
• Developing statistical and mathematical solutions to complex business problems, contributing to broader initiatives with minimal supervision
• Architecting data mining models and protocols to discern trends within extensive, intricate datasets, enhancing customer and product insights
• Deploying predictive analytics based on historical data to anticipate customer behavior and support strategic business decisions
• Synthesizing forecasts and strategic recommendations by applying data science to business data for impactful project support
• Advancing business decision-making by researching and applying novel data science principles and emerging analytical techniques
• Consistent exercise of independent judgment and discretion in matters of significance.
• Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary.
• Other duties and responsibilities as assigned.

• Requirements:

• Experience & Impact: 5-8 years of broad marketing experience both in business areas (e.g., Sales, Yield, Product Development) as well as multiple years in areas that apply machine learning to real-world business problems, with a track record of leading AI-ML model development and taking ideas from concept to production.

• Core Machine Learning: Deep mastery of AI-ML techniques like tree-based analysis (XGBoost, Random Forest), Regression, Classification, Natural Language Processing, and/or Time-series forecasting.

Standard evaluation metrics

Knowledge of how to evaluate models and how to work with business to set service levels (RMSE, MAPE, MAE, R-squared, etc.)

• Programming & SQL: Strong Python proficiency (pandas, NumPy, scikit-learn) and advanced SQL (window functions, query optimization, complex joins).

• Experimental Design & A/B Testing: Practical knowledge of designing, executing, and analyzing randomized control trials, power analysis, and hypothesis testing.

• Communication & Stakeholder Management: Proven ability to translate technical modeling decisions into actionable business insights for non-technical stakeholders.

• Bachelor’s degree: Mathematics, Statistics, Computer Science, Data Science, Econometrics, Psychometrics, or related mathematical field. Graduate degree preferred.

 

Nice to Have

• Production MLOps: Experience with model deployment frameworks (Docker, MLFlow, GIT, AWS CLI).

• Advanced Architecture: Hands-on experience with deep learning frameworks (PyTorch and/or TensorFlow)

Generative AI

– Familiarity with LLM fine-tuning and RAG pipelines.  Familiarity with Agentic.

• Distributed Stack: Familiarity with distributed computing platforms like PySpark.

• Domain Specialization: marketing-specific background (e.g., product analytics, demand trends and seasonality analysis, marketing feature attribution, pricing optimization, video content analysis).

• Databricks Infrastructure: Comfortable working within a databricks environment.

• Graduate Degree: Mathematics-related field.

• Employees at all levels are expected to:

• Understand our Operating Principles; make them the guidelines for how you do your job.
• Own the customer experience think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services.
• Know your stuff be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences.
• Win as a team make big things happen by working together and being open to new ideas.
• Be an active part of the Net Promoter System a way of working that brings more employee and customer feedback into the company by joining huddles, making call backs and helping us elevate opportunities to do better for our customers.
• Drive results and growth.
• Support a culture of inclusion in how you work and lead.
• Do what's right for each other, our customers, investors and our communities.

• Disclaimer: This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.

Skills

Analytical Solutions, Communication, Data Reporting, Data Science

Compensation

Pay Range: This job can be performed in California with a good faith estimated pay range upon hire of $108,442.04 - $144,589.39 USD.

This job can be performed in Illinois with a Pay Range of $98,583.68 - $162,663.07

Comcast intends to offer the selected candidate base pay within the posted range for this role at the time of posting dependent on job-related, non-discriminatory factors such as experience. The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.

Base pay is part of the Total Rewards that Comcast provides to compensate and recognize employees for their work.    Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus.  Additionally, Comcast provides best-in-class Benefits to eligible employees.  We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most.  That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the https://jobs.comcast.com/benefits compensation and benefits summary on our careers site for more details.

Education

Master's Degree

While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.

Certifications

(if applicable)

Relevant Work Experience

5-7 Years

Comcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Comcast will consider for employment applicants with arrest or conviction records in accordance with the requirements of applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Please note that federal state, or local laws and regulations may restrict or prohibit Comcast from hiring individuals convicted of certain crimes. Additionally, an applicant’s criminal history may have a direct, adverse, and negative relationship on the job duties of this position, which may result in the withdrawal of a conditional offer of employment.

• Experience & Impact: 5-8 years of broad marketing experience both in business areas (e.g., Sales, Yield, Product Development) as well as multiple years in areas that apply machine learning to real-world business problems, with a track record of leading AI-ML model development and taking ideas from concept to production.

• Core Machine Learning: Deep mastery of AI-ML techniques like tree-based analysis (XGBoost, Random Forest), Regression, Classification, Natural Language Processing, and/or Time-series forecasting.

Standard evaluation metrics

Knowledge of how to evaluate models and how to work with business to set service levels (RMSE, MAPE, MAE, R-squared, etc.)

• Programming & SQL: Strong Python proficiency (pandas, NumPy, scikit-learn) and advanced SQL (window functions, query optimization, complex joins).

• Experimental Design & A/B Testing: Practical knowledge of designing, executing, and analyzing randomized control trials, power analysis, and hypothesis testing.

• Communication & Stakeholder Management: Proven ability to translate technical modeling decisions into actionable business insights for non-technical stakeholders.

• Bachelor’s degree: Mathematics, Statistics, Computer Science, Data Science, Econometrics, Psychometrics, or related mathematical field. Graduate degree preferred.

• Production MLOps: Experience with model deployment frameworks (Docker, MLFlow, GIT, AWS CLI).

• Advanced Architecture: Hands-on experience with deep learning frameworks (PyTorch and/or TensorFlow)

Generative AI

– Familiarity with LLM fine-tuning and RAG pipelines.  Familiarity with Agentic.

• Distributed Stack: Familiarity with distributed computing platforms like PySpark.

• Domain Specialization: marketing-specific background (e.g., product analytics, demand trends and seasonality analysis, marketing feature attribution, pricing optimization, video content analysis).

• Databricks Infrastructure: Comfortable working within a databricks environment.

• Graduate Degree: Mathematics-related field.