About the Role :
We are seeking a Senior Manager - Measurement Programs to lead our Technical Implementation and Marketing Sciences teams.
This role sits at the intersection of marketing analytics, engineering and customer success, ensuring that Lifesights marketing measurement products are seamlessly deployed, customized, and continuously improved for our enterprise customers.
You will own the end-to-end delivery of measurement solutions - from implementation of data pipelines and API integrations to translating model outputs into business insights. This role demands strong technical skills (JS, APIs, SQL, data pipelines), deep understanding of marketing measurement science (MMM, attribution, incrementality), and the ability to manage and scale cross-functional teams that deliver customer impact.
Key Responsibilities :
Lead Platform Implementations :
- Oversee end-to-end deployment of Lifesights Marketing Measurement Platform for global clients.
- Design scalable implementation frameworks across multiple data sources - ad platforms, analytics systems, CRMs, and offline datasets.
- Ensure robust data collection, transformation, and ingestion using APIs, JavaScript SDKs, and SQL-based integrations.
Drive Measurement Excellence :
Collaborate with the Modelling & Product teams to ensure customer models meet high standards of statistical rigor, calibration, and interpretability.Translate complex model outputs (MMM, incrementality, attribution) into actionable business insights for marketers and executives.Guide clients in experiment design, causal validation, and performance evaluation frameworks.Bridge Technical & Marketing Sciences :
Lead and mentor a cross-functional team of data scientists, analysts, and implementation engineers.Identify opportunities to enhance platform capabilities through automation, API improvements, or new feature ideas emerging from real-world deployments.Partner with Product & Engineering to improve scalability, usability, and measurement accuracy across customer implementations.Customer Delivery & Governance :
Act as the senior point of contact for customer measurement programs, ensuring timelines, quality, and outcomes are consistently met.Establish internal best practices for QA, validation, and documentation across all measurement deployments.Develop repeatable playbooks and frameworks for onboarding, customization, and ongoing optimization.Insights, Experimentation & Feedback Loop :
Partner with customers to design and interpret A / B tests, geo-holdouts, and other causal measurement frameworks.Feed implementation learnings back into the product roadmap to continuously improve platform experience and feature set.Track and improve key metrics for deployment success, model reliability, and customer satisfaction.Who We're Looking For (Qualifications) :
Bachelors or Masters degree in Computer Science, Data Science, Statistics, or Engineering.8+ years of experience in marketing analytics, data engineering, or measurement science, with at least 2 years in a leadership role.Strong understanding of Marketing Mix Modeling, Attribution, Incrementality Testing, and Design of Experiments.Technical fluency with JavaScript (for tagging and SDKs), SQL, REST APIs, and data pipelines (ETL / ELT workflows).Working knowledge of statistical modeling frameworks (e.g., Bayesian regression, causal inference, time-series analysis).Proven experience leading cross-functional teams of data scientists, engineers, and marketing analysts.Exceptional communication skills to translate complex technical concepts into marketing and business outcomes.Demonstrated ability to manage enterprise clients and deliver scalable analytics solutions.Preferred Qualifications (Bonus Points) :
Experience deploying or managing measurement or attribution platforms (MMM, MTA, CDPs, analytics SDKs).Exposure to modeling libraries such as Meridian, LightweightMMM, Robyn, PyMC, or Stan.Understanding of MLOps practices, data pipelines (BigQuery, Snowflake, Airflow), and API integrations.Experience in AdTech, MarTech, or SaaS organizations.Familiarity with Agile delivery and sprint-based execution across technical and analytical teams(ref : hirist.tech)