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About the role
About Us
Lifesight is a pioneering, privacy-first Unified Marketing Measurement (UMM) platform which helps marketers measure, plan and optimise their marketing spend for growth. In a world of fragmented data, unreliable cookies, and outdated reporting, we empower modern businesses to achieve predictable, sustained growth by aligning marketing and finance on a single causal truth. We are at the forefront of Agentic Unified Marketing Measurement. Moving beyond siloed tools and post facto dashboards, our AI-driven causal engine combines Causal MMM, Incrementality testing and Incrementality Adjusted Attribution to create a finance ready marketing decision system. Key Responsibilities: ● Develop, validate, and deploy advanced regression-based frameworks to measure channel and campaign ROI. ● Research, adapt, and implement the latest methods from academic and industry papers in causal inference, Bayesian modeling, and time-series forecasting. ● Design and analyze A/B and multivariate experiments to drive actionable business insights. ● Collaborate with cross-functional teams (product, engineering, marketing science) to integrate measurement models into scalable systems. ● Continuously explore and apply the latest AI/ML techniques to maintain a competitive edge. ● Work closely with cross-functional teams to understand business needs and translate them into technical requirements. ● Mentor junior data scientists and contribute to fostering a culture of continuous learning and innovation. ● Establish and evangelize best practices in data science, experimentation, and statistical rigor across the organization. What we are looking for : Skills : ● Master’s or PhD in Computer Science, Statistics, Mathematics, or a related field. ● Strong expertise in causal inference techniques (DID, synthetic control, instrumental variables, Bayesian causal modeling, etc.) ● Proven track record in building complex regression-based models (hierarchical/multilevel, regularized, Bayesian regression etc). ● Hands-on experience with experimentation design, A/B testing, and uplift modeling. ● Proficiency in Python/R, SQL, and cloud-based data platforms. ● Experience in deploying models into production and working with large-scale data pipelines. ● Ability to read, interpret, and translate research papers into practical implementations. ● Excellent communication skills to explain complex models and results to both technical and business stakeholders. Experience : ● 3+ years of experience in data science or applied statistics, preferably in marketing analytics.
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