A professional profile built around curiosity, measurement, and continuous improvement.

I'm Harendra Sahu, an AI,Data Science, and Analytics leader with 16+ years of experience turning behavioural data into decisions, and decisions into revenue. I currently lead Data Science, BI & Analytics at Cimpress, where I own the digital measurement stack end-to-end and lead a multidisciplinary team spanning AI, Data Science, Data Engineering, Tagging, and Insights.

My journey into this space started at TCS, building KPI dashboards and analysing website traffic,the kind of ground-level work that taught me how raw clickstream data becomes a business signal. From there, I moved through Ducen, Infosys, and J. C. Penney, each step pulling me deeper into experimentation, behavioural analytics, and the architecture behind measurement itself, implementing Adobe Analytics from scratch, running funnel diagnostics on session-level data, and building the self-service reporting frameworks that let teams make decisions without waiting on a data team. At Cimpress, that trajectory came together. I architect incrementality and attribution frameworks (MMM, MTA, data-driven attribution) to separate real channel lift from noise, build behavioural clustering and propensity models on clickstream data to lift conversion and revenue, and run RFM-based churn models that turn prediction into marketing action. I have led a full GA4 migration across multiple global markets in three months, migrated tracking to server-side instrumentation for a privacy-first world, and unified web and CRM data through CDP integration to enable real personalization at scale.

What I care about

• Turning ambiguous questions into measurable problems.
• Building analytics systems that people can trust.
• Explaining technical ideas clearly.
• Using data without losing sight of human context.
• Learning through projects, experiments, and writing.

Current focus

What I enjoy most is the translation problem, taking a statistically rigorous model or a messy experiment result and turning it into a narrative that a marketing or product leader can act on with confidence. I care as much about why a metric moved as about the number itself, which is why I lean on causal methods; A/B testing, quasi-experiments, synthetic controls, over correlation whenever a real decision is riding on the answer. I am rounding out this experience with the Business Analytics & AI program at IIM Bangalore (cohort valedictorian), and I write here about the practical side of analytics, measurement architecture, experimentation design, attribution. Apart from work

Beyond work

Running is an important part of my life because it provides a practical laboratory for consistency,feedback, uncertainty, and long-term performance. I am training for Half Marathon and Full Marathon, it is a long-term commitment, and it teaches me lessons about patience, perseverance, and the value of incremental improvement. I write about my running journey here, sharing insights from training, races, and the mental discipline that running requires. It's a personal dataset of effort, recovery, and adaptation that complements my professional work with data.