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 In a world of fragmented data, unreliable cookies, and outdated reporting, we empower modern businesses to achieve predictable, sustained growth by aligning marketing and finance on a single causal truth.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.

● 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.