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About This Role
FreeWheel, a Comcast company, provides comprehensive ad platforms for publishers, advertisers, and media buyers. Powered by premium video content, robust data, and advanced technology, we’re making it easier for buyers and sellers to transact across all screens, data types, and sales channels. As a global company, we have offices in nine countries and can insert advertisements around the world. Job Summary
Freewheel is currently looking to recruit a Sr. Data Scientist to join our Audience Revenue Science Team. This role will be responsible for supporting product development efforts related to in\-depth data analysis, machine learning, AI, optimization methods, and statistical model building. This role will work very closely with engineering and product management staff to support the development of innovative approaches to the next generation of ad tech products.Job Description
- Implement ad tech solutions leveraging statistical models and machine learning methods
- Identify key data questions and conducting exploratory analyses
- Building forecasting methods for advertising use cases
- Applying optimization methods for ad scheduling applications
- Effectively leveraging key functionality in AWS and Spark\-based technologies
- Researching and applying new technologies and analytical methods.
- Applying advanced data visualization to provide key insights
- Working independently and as part of a broader team across multiple project
Desired Skills and Experience:
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- Bachelor’s degree in a technical field such as Data Science, Computer Science, Engineering, Business Analytics, Mathematics, Statistics, or Operations Research, Master’s or PhD a plus
- At least 3 of experience with Python, SQL, and analytical model implementation
- Experience with Optimization Models such as Linear and Nonlinear Programming
- Skilled at data mangling and manipulation
- Experience with data visualization tools and programming packages
- Strong analytical and problem\-solving skills; ability to work creatively in problem solving environment
- Experience using AWS or other cloud\-based platforms
- Proven ability to deliver on complex projects within deadlines
- Ability to communicate technical concepts to a non\-technical audience
- Strong interest in advertising technology
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.
- Respect and promote inclusion \& diversity.
- 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.
Comcast is an EOE/Veterans/Disabled/LGBT employer.
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.
Skills:
Machine Learning (ML); Business Analytics; Artificial Intelligence (AI); Model Building; Structured Query Language (SQL); Data Science; Python (Programming Language)
Salary:
National Pay Range: $93,062\.99 USD\-$218,116\.38 USD Illinois Pay Range: $98,879\.43 USD \- $191,942\.42 USD Colorado Pay Range: $104,695\.86 USD \- $200,667\.07 USD Hawaii Pay Range: $122,145\.18 USD \- $183,217\.76 USD Washington DC Pay Range: $133,778\.05 USD \- $200,667\.07 USD Maryland Pay Range: $110,512\.30 USD \- $200,667\.07 USD Minnesota Pay Range: $104,695\.86 USD \- $183,217\.76 USD New York Pay Range: $110,512\.30 USD \- $218,116\.38 USD Washington Pay Range: $104,695\.86 USD \- $209,391\.73 USD New Jersey Pay Range: $116,328\.74 USD \- $209,391\.73 USD Vermont Pay Range: $110,512\.30 USD \- $174,493\.11 USD Massachusetts Pay Range: $116,328\.74 USD \- $209,391\.73 USD California Pay Range: $104,695\.86 USD \- $193,881\.22
Comcast intends to offer the selected candidate base pay within this range, 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.
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 one 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 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.
Relevant Work Experience
5\-7 Years
Salary Context
This $104K-$209K range is above the median for Data Scientist roles in our dataset (median: $157K across 236 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,823 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Comcast, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $198,000 based on 808 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($157K) sits 21% below the category median. Disclosed range: $104K to $209K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Comcast AI Hiring
Comcast has 4 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer. Positions span Philadelphia, PA, US, San Francisco, CA, US, Washington, DC, US. Compensation range: $209K - $384K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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