Senior Machine Learning Engineer

Full-time contract (12 weeks) with potential to convert to permanent Remote (PST hours required) $70-$80/hour About Our Client Our client is a fast-moving media planning, buying, and analytics agency that builds and executes omnichannel paid media campaigns for both B2B and B2C brands. They are known for advanced measurement, strong strategic execution, and moving significantly faster than traditional agencies while maintaining a high level of transparency and client service. Role Overview Our client is seeking a senior Machine Learning Engineer / Data Scientist on a contract basis to support the development and delivery of a machine-learning–powered media measurement and optimization platform. This is a highly execution-oriented role focused on building, running, validating, and iterating on Bayesian marketing mix models to support active client engagements. You’ll work closely with analytics, data science, and media teams, translating complex statistical outputs into clear, actionable insights while contributing to the ongoing evolution of the modeling platform and underlying infrastructure. Responsibilities Build, run, and validate statistical and machine learning models for client reporting and optimization Translate complex analytical results into clear narratives for internal and client-facing teams Improve and extend Bayesian modeling approaches used for attribution and forecasting Maintain and contribute to a production-grade codebase, containerized workflows, and cloud infrastructure Operate within an AWS-based environment Work independently while managing multiple priorities and deadlines Provide guidance and mentorship to other data science team members Collaborate cross-functionally in a fast-paced, remote environment Requirements 8+ years of experience as a Data Scientist, with a strong background in advertising analytics Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, or a related field Advanced Python skills with solid foundations in data structures, algorithms, and OOP Deep experience with Bayesian modeling (ideally PyMC and pymc-marketing) Proficiency with SQL, Pandas, and standard ETL practices Experience with Ray, containerization tools (Docker or Podman), Git, and Terraform Familiarity with ML frameworks such as scikit-learn, TensorFlow, or PyTorch Strong knowledge of econometrics and statistical modeling Proven ability to work independently and communicate effectively in a remote setting Experience with marketing mix modeling (MMM), experimentation, and media measurement required Strong organizational skills and attention to detail Must work PST hours Candidates must reside in one of the following states: AZ, CA, CO, CT, IL, MA, NJ, NY, OR, SC, TX, WA #J-18808-Ljbffr