Description
**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
Job Type: Full\-time
Work Location: Remote