Data Science Engineer

Antenna is the leading provider of data and analytics for subscription media services in the U.S. Antenna's standardized metrics, competitive benchmarks, syndicated insights, and market intelligence are trusted by some of the most recognized and respected brands across media and entertainment sectors. Using a proprietary AI-powered approach, Antenna connects subscription activities with real consumer viewership to provide services, studios, and creators with an unmatched, market-wide view of subscriber behaviors to better understand acquisition, retention, and engagement.

We're looking for a talented Data Scientist with expert Python skills and experience in processing large amounts of data to join our team. You'll be a key player in designing, building, and making our main data pipelines and ML systems (that power our advanced analytics and machine learning models) able to handle more. You'll work closely with data scientists and engineers to create strong, efficient, and scalable systems. If you love solving complex technical problems, building production-ready data systems, and want to make a big impact on a data-driven company, this job is for you

Antenna is a remote-first company, and we are looking for candidates who can work during US business hours. Preferably, you should be based in a US time zone (Eastern, Central, Mountain, or Pacific). You will report to the Data Science Lead.

What You'll Do

• Design, develop, test, and maintain strong and scalable data pipelines using Python and tools for large-scale data processing (like Spark, Dask, or similar on GCP)
• Design and take ownership of key parts of our ML systems, making sure they are reliable, efficient, and can grow
• Set up and manage MLOps practices, including automatic updates for machine learning models (CI/CD), model monitoring, and automated launch plans
• Improve and manage data processing jobs on cloud platforms (GCP: Dataproc, BigQuery, Cloud Run, Cloud Build)
• Work with data scientists to get machine learning models ready for production and connect them to our data systems
• Write detailed documents for the system designs, code, and systems you create and manage
• Fix complex technical problems in data systems that run on many computers and in ML pipelines

Who You Are

• You have 3-5+ years of work experience in software engineering, with a strong focus on data engineering, ML engineering, or building applications that use a lot of data
• You are an expert in Python, with a strong understanding of object-oriented design, software system design, and experience building high-quality, testable code for production
• You have strong, hands-on experience with tools for handling large amounts of data like Apache Spark (PySpark), Dask, or similar
• You have solid experience with cloud platforms (GCP is highly preferred). This includes putting services live, managing them, making them handle more users (e.g., Docker, Cloud Run, GKE), and working with large data systems (e.g., Dataproc, BigQuery)
• You have strong SQL skills and experience working with large, complex datasets
• You have a deep understanding of machine learning ideas, the full process of creating a model, and MLOps principles
• You are an excellent problem-solver, good at fixing complex issues in systems that run on many computers, and making them perform better and handle more data
• You explain complex technical ideas and system design decisions clearly and effectively in English
• Advanced English proficiency (B2-C1); Excellent communication, teamwork, and consulting skills
• You are passionate about building strong, scalable systems and are eager to guide and work with a team
• You care deeply about code quality, system reliability, and writing good documentation

Bonus

• Experience in or passion for the Subscription Economy, especially in media and entertainment
• Deep knowledge of specific GCP services like Dataproc, Dataflow, Cloud Composer, Vertex AI, or Kubernetes Engine
• Experience building and maintaining Python code (libraries) used by many, or contributions to open-source projects
• Advanced knowledge of MLOps tools and ways to manage workflows (e.g. Cloudbuild, CloudRun)

Antenna's Tech Stack (Required Proficiency)

• Languages: Python (expert), SQL (strong)
• Large-Scale Data Processing: Apache Spark/PySpark (or similar like Dask)
• Cloud Platform: Google Cloud (Dataproc, BigQuery, Cloud Storage, Cloud Run, Cloud Build, GKE - strong experience expected)
• Version Control: Git (expert)
• MLOps & Orchestration: Familiar with tools like Airflow, Kubeflow, Vertex AI Pipelines
• Containerization: Docker, Kubernetes
• Data Analysis Libraries: Pandas, NumPy (very good with these)
• Machine Learning: scikit-learn, TensorFlow/PyTorch (understand how to get them to production)
• AI Tools: Claude, Gemini, OpenAI offerings

Antenna Benefits

• Work from anywhere, during US business hours
• Competitive compensation, including participation in Antenna equity program
• Mentorship from experienced executives
• Opportunity to grow and impact a rapidly growing start up 
• Travel to In-person team off-sites (visa-permitting)
• And more

Antenna is the leading provider of data and analytics for the U.S. Subscription Economy. Our standardized metrics, competitive benchmarks, syndicated insights, and market intelligence are used by some of the most trusted brands across media and entertainment sectors to better understand subscriber behavior and successfully navigate the rapidly changing consumer subscription landscape.

Founded in 2019 by Jonathan Carson, a successful serial entrepreneur with deep roots in data and analytics, and Rameez Tase, a seasoned executive in media and analytics, Antenna's mission is supported by top investors with global expertise in media and technology: Raine Ventures, BDMI, UTA Ventures, and many more. Antenna is powered by a dedicated group of individuals who are intellectually curious, passionate about service, and committed to supporting the needs of Antenna clients and each other every day. As a small remote-first team, Antenna team members have the opportunity to work alongside senior leaders and professionally grow with an early-stage team.