Machine Learning Engineer, Spectrum Strategy Group
Employment Type: Full-Time
Workplace Type: Hybrid
Location: Santa Monica, CA
Industry: Advertising Services, Broadcasting, Media
Compensation: $140,000 - $200,000 + annual bonus
Job Description:
As the Machine Learning Engineer in the Spectrum Strategy Group, you will take on a pivotal role in our organization, driving ML projects that have the potential to revolutionize spectrum auctions while managing critical data related to our initiatives.
Machine Learning Responsibilities:
• Interference Relationship Modeling: Build a robust interference relationship model. Select and train a model on the complex interference patterns between TV stations defined in the FCC's Interference_paired.csv and Domain.csv files (proprietary datasets). Leverage machine learning techniques to ensure minimal interference between stations during the repacking process.
• Spectrum Compression and Efficiency: Optimize the TV spectrum band using standard compliant, SOT compression codecs. Select and train a model on the characteristics of TV signals and advanced compression codecs such as H.265/MPEG4. Identify the most efficient ways to compress the spectrum band, freeing up significant spectrum for future auctions. Additionally, you will play a key role in data management and analysis:
Data Analysis Responsibilities:
• Data Integration: Extract, transform, and load (ETL) data from various sources into the database, ensuring data accuracy and consistency.
• Database Development: Develop a comprehensive SQL database to store ETL data, pairwise interference data, domain files, simulation data, and (possibly) the FCC's LMS database.
• Data Analysis: Perform in-depth data analysis to extract insights, identify patterns, and assess interference profiles using SQL, Python, and other data analysis tools (shared responsibility).
• Data Visualization: Create compelling reports and dashboards to present analytical findings, allowing stakeholders to make informed decisions. Folium is a favored solution (shared responsibility).
• Automation: When relevant, implement automation scripts using Python or similar tools to streamline data processing and analysis tasks.
• Documentation: Maintain detailed documentation of the data warehouse structure, data sources, and analysis methodologies (shared responsibility).
• Collaboration: Collaborate with cross-functional teams, including spectrum experts, software developers, and regulatory specialists, to ensure data-driven decision-making.
Required Qualifications:
• Master's degree in Machine Learning, Data Science, or equivalent experience.
• Strong proficiency in SQL for database design and management.
• Proficient with Python programming and skilled with Python libraries used for ML modeling and Data Science (i.e. PyTorch, NumPy, SciPy, TensorFlow, Pandas, Theano, Matplotlib)
• Proficiency in data visualization tools like Tableau, Power BI, or similar.
• Excellent communication and collaboration skills.
• Attention to detail and the ability to work independently
Desired Qualifications:
• Understanding of FCC regulations, particularly related to spectrum auctions and interference analysis (TVStudy would be a significant plus).
• Previous experience with spectrum auctions, specifically FCC Incentive Auction, is a significant plus.
Other Duties:
Please note this job description is not designed to cover or contain a comprehensive listing of
activities, duties, or responsibilities required of the employee for this job. Duties, responsibilities, and activities will evolve as the project matures.
All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance
