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About This Role
Who we are:
Mediacom Communications Corporation is the 5th largest cable operator in the United States and the leading gigabit broadband provider to smaller markets primarily in the Midwest and Southeast. With a team of over 3,900 dedicated professionals, we are committed to bridging the digital divide between America's major cities and its smaller regions. Through its fiber-rich network, Mediacom offers high-speed data, video, phone, and mobile services to over 3 million households and businesses across 22 states. The company delivers scalable broadband solutions to commercial and public-sector customers of all sizes through Mediacom Business and sells advertising and production services under the OnMedia brand.
At Mediacom, we are passionate about growth and innovation. We offer faster, more reliable internet service, expanded digital and HD TV choices, and advanced home security and phone solutions. As we continue to expand, we strive to remain at the forefront of delivering cutting-edge entertainment, communications, and internet products. This year, we proudly launched our new mobile phone network, further enhancing our commitment to providing innovative and comprehensive services.
To achieve this, Mediacom Communications seeks talented professionals to partner with us to meet these challenges and realize what we can imagine. Take the next step toward a dynamic and rewarding career with Mediacom Communications. Learn more about us at mediacomcable.com
Position Overview:
The Data Scientist / AI Engineer will collaborate with a multidisciplinary team across marketing, sales, networking, and leadership to develop data-driven, machine learning, and AI-powered solutions that improve business performance, customer experience, advertising effectiveness, and customer retention. This role is responsible for designing, building, and deploying predictive models, generative AI applications, and agentic AI solutions using modern AI frameworks and enterprise data platforms. As a Data Scientist / AI Engineer, you will own the full lifecycle of AI and machine learning solutions, from data discovery and solution design to development, deployment, monitoring, and optimization. Experience with machine learning, large language models (LLMs), retrieval-augmented generation (RAG), AI agents, prompt engineering,
and production tuning is required.
Company Benefits:
At Mediacom, we believe that your success is our success, providing you the Power to Succeed in your career. That's why we offer a comprehensive benefits package designed to support and enhance both your personal and professional life. You'll find many advantages to joining the Mediacom team such as:
- Comprehensive Health Coverage: Including health, vision, and dental insurance to keep you and your family healthy.
- Education Enrichment: Up to $5,000 per year for professional development and educational advancement.
- 401(k) Retirement Plan: With a generous company match to help you plan for your future.
- Paid Time Off: Including vacation, holidays, and flexible paid time off to ensure work-life balance.
- Employee Discounts: Enjoy discounts on Mediacom services where available, or receive a reimbursement for internet/cable services in areas where Mediacom isn’t offered.
- Ongoing Training and Professional Development: To help you grow in your career and achieve your professional goals.
- And Much More: Additional benefits and perks!
Join the Mediacom team and experience how we’re committed to your career growth and overall well-being.
Position Responsibilities:
- Gather requirements and write functional design documents
- + Analyze data to discover trends and patterns + Use predictive modeling to improve customer experience, reduce customer churn, optimize ad targeting, and drive other business outcomes + Design, prototype, and support AI agent-based solutions using LangChain and LangGraph, including retrieval-augmented generation, tool/function calling, workflow orchestration, API integration, and enterprise data source connectivity + Develop and maintain scalable data pipelines, analytics workflows, machine learning solutions, and AI solutions using Databricks + Develop processes and tools to monitor and analyze model performance and data accuracy + Implement AI observability, model monitoring, and feedback loops to continuously improve AI solutions + Act as a liaison between business users and technical team members, including outsourced team members + Process structured and unstructured data + Collaborate with business stakeholders, data engineers, software developers, and external partners to deliver AI-driven products and capabilities
- + Provide production support for AI and analytics platforms, identify root causes of issues, and implement mitigation strategies
Position Requirements:
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related field is required; a master’s degree in one of these fields is preferred
- + At least 3 years of hands-on experience in AI engineering, machine learning engineering, data science, or a related role + Proven track record of implementing advanced machine learning algorithms and AI solutions using advanced statistical analysis techniques and concepts + Knowledge of machine learning techniques, deep learning, model evaluation, and MLOps best practices + Excellent Python, SQL, and database skills + Hands-on experience with Databricks, notebook development, Spark-based processing, and ML workflow support + Experience developing AI agents or agentic AI solutions using LangChain, LangGraph, large language models, prompt engineering, retrieval-augmented generation, vector databases, APIs, and enterprise data sources is preferred + Understanding of AI governance, security, responsible AI, model monitoring, and prompt engineering best practices + Experience deploying AI solutions in cloud environments such as Azure, AWS, or Google Cloud is preferred + Strong communication skills and the ability to build positive, professional, and productive business relationships with business users + Proven ability to manage multiple projects simultaneously and produce tangible results
- + Self-sufficient and able to work independently
Disclaimer: The salary range for this position is $100,000- $135,000. When making a job offer, we consider several factors in our determination, such as years of related work experience, relevant skills and qualifications; education level, and certifications/licenses.
Our Awards: Mediacom is proud to have received the following recognitions: 2025, 2024, 2023, 2022, and 2021 Best Managed Companies, 2019 Best Company for Women to Work, 2017 Best Company for People of Color and Women to Work, and Content & Connectivity Human Resources (C2HR)’s 2021 Social Impact Award.
Who you are matters here: Mediacom Communications Corporation is an Equal Opportunity/Affirmative Action Employer. We are committed to Equal Employment Opportunity (EEO) for all employees and applicants for employment. Mediacom Communications Corporation prohibits discrimination and harassment based on race, national origin, religion, age, color, sex, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. These protections extend to all employment policies, practices, and actions, including, but not limited to, recruitment and hiring; job assignments; performance management; rewards; promotions; training and development; reassignments; discipline; and separations.
#Li-Hybrid
Mediacom endeavors to make mediacomcable.com/careers accessible to any and all users. If you would like to contact us regarding the accessibility of our careers website, please contact [email protected] or dial 845-443-2408*. Any inquiries regarding employment application status, resume submittal, open positions and any other general inquiries will not receive a response.*
Salary Context
This $100K-$135K range is in the lower quartile for Data Scientist roles in our dataset (median: $167K across 150 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 8,943 AI roles we're tracking, Data Scientist positions make up 4% of the market. At Mediacom Communications Corporation, 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 $190,000 based on 1,406 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($117K) sits 38% below the category median. Disclosed range: $100K to $135K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Mediacom Communications Corporation AI Hiring
Mediacom Communications Corporation has 1 open AI role right now. They're hiring across Data Scientist. Based in Blooming Grove, NY, US. Compensation range: $135K - $135K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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