Data Scientist (Marketing / Commercial )

We are looking for a Marketing / Commercial Data Scientist to build the intelligence layer of our Session Analyzer product — including scoring systems, segmentation, recommendation models, and causal measurement frameworks for pharmaceutical marketing teams.

This role sits at the intersection of behavioral data, machine learning, and marketing analytics. You will work end-to-end: from raw event data → feature engineering → modeling → production pipelines → business insights.
 

You’ll collaborate closely with Product and Tech Leads to turn complex behavioral signals into actionable commercial intelligence.

🛠 Requirements

• 5+ years in Data Science / Analytics
• Experience building production ML systems
• Strong ownership of end-to-end data science workflows
   

Technical Skills

• Python, SQL, PostgreSQL
• GCP / BigQuery /ClickHouse
• Data pipelines & feature engineering
• Experience with LLM-based agents / AI workflows
• Event-level / session analytics
• Aggregation modeling
• Propensity / engagement modeling
• Segmentation
• Recommendation systems
• Model evaluation & monitoring
• Experience in AdTech / MarTech / Marketing Analytics
• Marketing attribution & measurement
• Behavioral / clickstream / pixel data
   

🧠 What You’ll Work On

🔹 Behavioral & Scoring Models

• Build propensity and engagement models (e.g., prescribing likelihood, rep response, content affinity)
• Develop switch / churn-style models and brand adoption predictions
• Design segmentation frameworks based on behavioral and profile data
   

🔹 Recommendation & Personalization

• Build recommendation systems using session and event-level data
• Model multi-channel engagement and content affinity
   

🔹 Causal Inference & Attribution

• Design and implement marketing attribution models
• Apply causal inference techniques (uplift modeling, incrementality testing, treatment/control analysis)
• Connect marketing exposure → downstream outcomes
   

🔹 Data & Feature Engineering

• Build feature pipelines from event/session data (clicks, scroll depth, dwell time, downloads, video plays)
• Create aggregated feature tables and scoring datasets
• Work with high-volume data systems (e.g., ClickHouse, BigQuery)
   

🔹 Production & Data Quality

• Deploy and maintain production ML pipelines
• Implement data validation, monitoring, anomaly detection, and drift tracking
   

🔹 AI & Insight Automation

• Build LLM-powered workflows for:
  • Automated insight generation
  • Data diagnostics
  • Structured analytical outputs (e.g., JSON)
     

🎯 What Success Looks Like

• You build reliable scoring systems used in production
• Your models drive measurable marketing impact
• You translate behavioral data into clear, actionable insights
• You help evolve the system toward real-time intelligence & automation
   

🧪 Interview Process

• Screening Interview
• Technical Interview
• Bar Raiser