Senior Analytics Manager

Role Overview As a Senior Analytics Manager, you will drive analytics-led decision-making, create high impact insight narratives, manage client facing discussions, and accelerate analytics workflows through automation and generative AI. The role includes a light data engineering component - building ETL/ELT pipelines, ensuring data quality, and enabling scalable data foundations for analytics, in partnership with engineering teams. 6-10 years of experience in data science, analytics, or marketing science , ideally within media, consulting, or digital marketing analytics environments. Strong proficiency in: + Python (pandas, scikit learn, ML frameworks for modelling). + SQL and cloud data warehouses ( BigQuery , Snowflake, Synapse, Redshift). + Google Cloud Platform (GCP) - especially BigQuery, GCS, Cloud Composer. + Data Visualization & BI Tools , specifically: - Power BI - Google Data Studio / Looker Studio - Creating dashboards for reporting, insight delivery, and campaign measurement. Must-have analytical expertise: + Media Mix Modelling (MMM) + Multi-touch modelling / attribution principles + Halo and incrementality analysis + Regression & forecasting models + Predictive modelling + Marketing analytics & media measurement Experience with advertising, campaign, impression, and media spend datasets. Familiarity with generative AI tools (HuggingFace, LangChain, OpenAI) to accelerate workflows. Experience with ML lifecycle monitoring, retraining, and performance tracking. Strong communication and storytelling ability - able to translate analytical outputs into business language. Strong stakeholder and client management skills. High analytical curiosity, attention to detail, and problem-solving strength. Collaborative mindset across analytics, engineering, product, and strategy teams. Knowledge of broader media measurement approaches: MMM, MTA, competitive benchmarking, ROI modelling, influencer analytics, channel performance analysis. Experience with causal inference (uplift modelling, Shapley, double ML). Familiarity with feature stores, realtime/batch ML pipelines, MLflow/Seldon. Exposure to data quality frameworks like Great Expectations or Monte Carlo. Knowledge of containerization (Docker/Kubernetes) and MLOps practices. Highly proactive and adaptable, thriving in fast-paced agency environments. Strong collaborator with cross-functional teams. Ability to guide teams toward analytical excellence and influence decision-making.