Senior Data Scientist – MMM ID71005

Job Description

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

Requirements
5–7 years of professional data science experience, emphasizing time-series analysis, prior distributions, or high-complexity attribution modeling. Hands-on Meridian Exposure: Clear, verifiable experience applying or testing the Meridian MMM framework on real-world datasets. Production Python Engineering: Strong backend proficiency using Python (specifically leveraging tools that reinforce static type systems and structured schemas). Terminal-Centric Fluency: Absolute comfort operating entirely inside standard Mac/Linux terminal infrastructure (using Bash, shell utilities, and text-based tools). Data Layer Familiarity: Proficiency writing advanced queries to extract and prepare data housed in cloud systems (such as AWS Athena or PostgreSQL environments). Opinionated Communication Skills: Strong soft skills, specifically the assertiveness to defend a technical or mathematical methodology against a project shortcut that threatens calculation validity.