Senior Data Scientist

Role 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.

Qualifications

• 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.

Requirements

• 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.

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.