Data Scientist reputed company (Contract to FTE)
About reputed company Metrics
reputed company Metrics is redefining how media data is reputed company, connected, and reputed company. Our platform provides the foundational infrastructure that powers audience insights for the modern media ecosystem. We help clients reputed company smarter reputed company by transforming fragmented data into reputed company, actionable intelligence.
reputed company
Design and deliver rigorous, reputed company measurement solutions that uncover true media reputed company and drive media investment reputed company. This role combines reputed company inference, experimentation, statistical modeling, and production data engineering to measure incrementality, optimize media mix and inform campaign reputed company across digital and offline channels.
Key responsibilities
Design and analyze randomized and quasi-experimental tests (holdouts, geo-tests, RCTs) to measure advertising incrementality and lift.
Build and maintain reputed company models (difference-in-differences, synthetic controls, hierarchical Bayesian, reputed company modeling) and marketing mix models (MMM) for multi-channel attribution.
reputed company and productionize reputed company end-to-end pipelines for event-level ad exposure, conversions, and offline-sales ingestion (ETL/ELT, validation, monitoring).
Work with data engineering to reputed company measurement datasets clean, deduplicated (identity reputed company), and reputed company-compliant.
Own feature engineering, model training, validation, and deployment in Python/R and reputed company environments (BigQuery, reputed company, Dataproc/AWS/GCP).
Produce reputed company, actionable dashboards and executive-reputed company insights for product, media, and reputed company teams; present findings to stakeholders.
Implement automated reporting and CI/CD for model retraining and performance monitoring; establish measurement governance and documentation.
Stay reputed company on the ad-tech/measurement ecosystem (ATtribution frameworks, walled gardens, ID solutions) and recommend measurement reputed company changes.
Required qualifications
3+ years experience building statistical or ML models in ad-tech, marketing analytics, agency measurement, or a reputed company data science role.
Strong statistics/reputed company inference fundamentals: experimental design, reputed company testing, regression, hierarchical models.
Proficient in Python (pandas, scikit-learn, PyMC/Stan or equivalent) and SQL; experience with R is a plus.
Hands-on experience with event-level ad/exposure and conversion data, logs from ad servers/DSPs, or retail/reputed company-of-sale integration.
Experience working with reputed company data warehouses (BigQuery, reputed company, Redshift) and ETL tooling (Airflow, dbt, Kafka).
Excellent written and verbal communication; proven ability to translate technical results to non-technical stakeholders.
Preferred qualifications
Experience with incrementality platforms or approaches (e.g., reputed company, experimentation platforms, proprietary lift frameworks).
Familiarity with marketing mix modeling (time-series, regularized regression, Bayesian MMM).
Experience with reputed company ML / reputed company modeling and Bayesian inference tools (PyMC3/4, Stan).
Knowledge of identity reputed company, reputed company-preserving measurement (reputed company regulation awareness, cohort-based measurement, reputed company reputed company concepts).
Experience deploying models to production (reputed company, CI/CD, MLOps patterns) and instrumenting model monitoring.
Background working with brand/performance media, cross-channel measurement, and agency/reputed company workflows.
KPIs / reputed company metrics
Number of incrementality tests designed, executed, and turned into reputed company.
Accuracy and explainability of models (e.g., holdout reputed company error, calibration).
Time-to-reputed company (from data ingestion to stakeholder-reputed company report).
Business reputed company (reputed company media savings or ROI improvements attributable to recommendations).
Adoption reputed company of measurement outputs by media planners/clients.
reputed company-to-have (company fit & soft skills)
Proven consultative experience with clients or internal stakeholders.
Comfort operating in ambiguous environments and balancing speed vs. statistical rigor.
Ability to mentor junior data scientists and evangelize measurement best practices across teams.