Data Scientist - Future Opportunity / Talent Pool

Please note: This job post is intended for future opportunities and talent pool building purposes only. We are not actively hiring for this position at the moment, but we’d love to connect with talented professionals who may be a great fit for upcoming opportunities at Monks.

Title: Semi-Senior Data Scientist

Job Family/Job Family Group: Data & Analytics

Job Level: Mid-Senior Level (Semi-Senior)

About the Role

As a Semi-Senior Data Scientist, you will help develop and maintain our data infrastructure and visualization layers for digital marketing and advanced media performance analytics, collaborating closely with Analytics, Data Science, and Solutions Engineering teams. In this role, you will bridge the gap between raw data and decision-ready insights by building robust pipelines, warehouse layers, and interactive dashboards to measure cross-channel media effectiveness across leading global brands. We are looking for someone who is curious, technically rigorous, highly collaborative in cross-functional environments, and passionate about turning complex data streams into strategic, actionable business recommendations.

Responsibilities:

Build and maintain scheduled ingestion pipelines to extract spend, impression, and conversion data from major media platform APIs (Google Ads, YouTube, Meta, TikTok, LinkedIn) and first-party sources into BigQuery.

Design and manage the BigQuery data warehouse layer, implementing partitioning, clustering, and incremental models to ensure modeling datasets remain reproducible and query-efficient.

Develop robust transformation logic that cleans, normalizes, and joins cross-platform data into modeling-ready tables for Marketing Mix Modeling (MMM) frameworks and geo/matched-market experiments.

Implement rigorous data quality controls, schema validations, freshness checks, and anomaly detection alerts to capture failures and data drift proactively.

Integrate and maintain Data Manager APIs and GA4-to-BigQuery pipelines to strengthen first-party signal ingestion across the measurement architecture.

Manage supporting cloud infrastructure (scheduling, service accounts, access controls, cost monitoring) while documenting lineage and operational runbooks.

Build and maintain interactive reporting dashboards (Looker Studio, Looker, GA4 Omni Insights) that present media performance metrics, measurement results, and test readouts.

Deliver serving and visualization layers that translate MMM, incrementality, and geo-test outputs into decision-ready business views.

Collaborate with internal and client-facing teams as a consultative resource, using data visualization techniques to articulate complex data models and foster data-driven experimentation roadmaps.

About You

The essentials:

Bachelor’s degree in Computer Science, Systems Engineering, Mathematics, Statistics, Physics, or a related quantitative field.

2+ years of hands-on experience in data engineering, analytics engineering, or data warehousing.

Proven proficiency in Google Cloud Platform (GCP), specifically Google BigQuery, Cloud Composer/Airflow, and GCP security and access controls.

Strong programming proficiency in SQL and Python for data manipulation, cleansing, and transformation.

Hands-on experience extracting data from media platform APIs (Google Ads, Meta, TikTok, LinkedIn) and digital analytics platforms (GA4).

Experience building self-serve, interactive dashboards using Looker Studio, Looker, GA4 Omni Insights, or equivalent BI tools.

Collaborative mindset with a passion for continuous learning, knowledge sharing, and solving complex business challenges through analytics.

Advanced or fluent English communication skills (written and verbal) to collaborate with global, distributed teams and clients.

Not a Must but a Plus:

Familiarity with Marketing Mix Modeling (MMM) frameworks (such as Meridian) and incrementality or geo-testing methodologies.

Hands-on experience building scalable ETL/ELT pipelines using tools like dbt, Apache Beam, Cloud Functions, or Pub/Sub.

Experience with infrastructure-as-code (e.g., Terraform) or certifications in multi-cloud environments (AWS, Microsoft Azure).

Ability to translate complex analytical architectures and advanced methodologies to non-technical stakeholders to guide strategic decisions.

At Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants from all backgrounds who are excited to contribute to our mission.