The Role
Drive statistical execution and algorithmic validation of Meridian MMM frameworks, build heuristic backup models for noisy/time-series marketing data, ingest structured pipeline data, run experiments, write advanced SQL against cloud data stores, and collaborate with engineering to deliver multi-objective spend recommendations.
Summary Generated by Built In
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
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.
WHAT YOU WILL DO
- 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.
MUST HAVES
- 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.
PERKS AND BENEFITS
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location
Skills Required
- 5-7 years 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, leveraging tools that reinforce static type systems and structured schemas.
- Comfort operating entirely in Mac/Linux terminal infrastructure using Bash, shell utilities, and text-based tools.
- Proficiency writing advanced queries and preparing data in cloud systems such as AWS Athena or PostgreSQL.
- Strong communication skills with the assertiveness to defend technical or mathematical methodology.
- Upper-intermediate English level.
- Familiarity with containerized applications using Docker or basic Kubernetes paradigms.
- Practical knowledge of structural time-series models, Bayesian inference, or custom MCMC configurations.
- Experience with multi-account privacy boundaries and strict client data partitioning compliance.
- Background analyzing digital platform performance APIs (Google Ads, Amazon Advertising, YouTube Data).
Am I A Good Fit?
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The Company
What We Do
AgileEngine is a privately held company established in 2010 that builds dedicated teams of designers and developers. We turn good ideas into awesome software that people actually want to use. Some of the biggest names and the hottest startups around the world chose us to build their tech.
