> Markdown version of [/jobs/ext/1801479-senior-data-scientist-mmm-id71005](https://www.wearedevelopers.com/jobs/ext/1801479-senior-data-scientist-mmm-id71005). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - MMM ID71005 - **Company:** AgileEngine, LLC - **Location:** McLean, VA, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Google AdWords, Amazon Web Services, Bash Shell, Data Systems, Linux, Python (Programming Language), PostgreSQL, Type Systems, Cloud Platform System, Sql Optimization, Backend, Containerization, Kubernetes, Markov, Data Pipelines, Google Meet, Docker - **Published:** July 31, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p8u11qzqvo ## About the Role If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!, * 5-7 years of professional data science experience, emphasizing time-series analysis, prior distributions, or high-complexity attribution modeling. * Clear, verifiable experience applying or testing the Meridian MMM framework on real-world datasets. * Strong backend proficiency using Python, specifically leveraging tools that reinforce static type systems and structured schemas. * Absolute comfort operating entirely inside standard Mac/Linux terminal infrastructure using Bash, shell utilities, and text-based tools. * Proficiency writing advanced queries to extract and prepare data housed in cloud systems such as AWS Athena or PostgreSQL environments. * Strong communication skills, specifically the assertiveness to defend a technical or mathematical methodology against a project shortcut that threatens calculation validity. * Upper-intermediate English level. NICE TO HAVES * Familiarity with containerized applications managed under Docker or basic Kubernetes infrastructure paradigms. * Practical knowledge of structural time-series models, Bayesian inference techniques, or custom Markov Chain Monte Carlo (MCMC) configurations. * Prior experience dealing with multi-account privacy boundaries and strict compliance mandates regarding client data partitioning. * Background in analyzing digital platform performance APIs, such as Google Ads, Amazon Advertising, or YouTube Data systems. ## Description We are looking for a Senior Data Scientist to drive rigorous statistical execution, multi-goal tuning, and algorithmic validation of client-specific Meridian MMM frameworks, translating noisy marketing signals and low-resolution data matrices into trusted, multi-objective spend recommendations. You will formulate heuristic baseline models for high-variance datasets, ingest structured data from upstream pipelines for client-isolated experimentation, and apply Python with advanced SQL against AWS Athena and PostgreSQL environments., * Expand framework configurations to natively factor in multi-layered client objectives, such as separating mid-funnel brand awareness metrics from immediate revenue generation targets. * Formulate robust heuristic models and pragmatic backup strategies to generate valid analytical insights when working with limited or high-variance customer datasets. * Safely ingest highly structured fields derived from upstream single source of truth data pipelines to execute client-isolated experimentation. * Leverage modern AI-assisted IDE tools to expedite data transformations while applying strict analytical validation to catch tool errors or structural flaws before deployment. * Collaborate daily with internal engineering cross-functions via Slack and Google Meet to rapidly resolve ambiguous pipeline requirements or technical dependencies. ## Related Videos - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Rules, Heuristics, or LLMs? 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