We are seeking a mid-level Data Scientist to work closely with a leading insurance/financial services client in Kuala Lumpur. The role focuses on developing and implementing lead scoring models and propensity models to optimize customer engagement and revenue via agents. You will work closely with business stakeholders to understand the data, translate business requirements into analytical solutions, and deliver actionable insights.

Key Responsibilities:

• Develop lead scoring models to rank customer leads and improve agent conversion rates.
• Build and implement propensity models to predict customer behavior and inform business decisions.
• Collaborate with client stakeholders to understand business context, data sources, and key metrics.
• Extract, clean, and analyze large datasets to generate actionable insights.
• Work hands-on with coding and analytics tools (Python, Databricks).
• Communicate findings effectively to both technical and non-technical stakeholders.

Ideal Profile:

• Mid-level experience (5 years) in data science, analytics, or related roles.
• Strong proficiency in Python and working in Databricks or similar platforms.
• Comfortable bridging technical implementation with business understanding.
• Experience with insurance or financial services data is a plus.
• Strong analytical, problem-solving, and communication skills.

Engagement Details:

• On-site in Kuala Lumpur, Malaysia.
• Duration: 4–8 weeks (short-term, project-based).
• Start: ASAP