Company Description IKASI AI specializes in helping enterprises make smarter decisions with causal AI by understanding the reasons behind people's actions. This deeper insight leads to more accurate offers and recommendations, generating significant profits and gaining market share. IKASI focuses on maximizing customer lifetime value through increased engagement and optimized product offers while maintaining data security, privacy, and integrity. Role Description This is a full-time remote role for a Data Scientist at IKASI AI. You will work closely with product, and engineering teams to support data-driven decision-making through robust, production-grade causal modeling. This role requires hands-on experience deploying causal inference models at scale, and a strong academic foundation in causal reasoning. Responsibilities • Design, implement, and productionize causal inference models • Analyze experiments and quasi-experiments • Collaborate with engineering to integrate models into production systems • Communicate findings clearly through presentations, dashboards, and documentation • Research new causal modeling techniques Minimum Qualifications • Ph.D. or Masters in Statistics, Economics, Computer Science, or a related quantitative field • 1+ years industry experience post Ph.D, 3+ years industry experience for Masters • Must have completed formal coursework in causal inference or econometrics at university level • Experience with causal inference modeling and experimental design • Solid knowledge of machine learning and statistical inference • Strong communication skills for translating complex concepts to non-technical audiences • Detail-oriented with excellent documentation and reporting skills • Proficient in Python or R Preferred Qualifications • Previous experience in a similar role is a plus • Familiarity with model monitoring and MLOps tools • Publications, blog posts, or open-source contributions related to causal inference • Experience with state-of-the-art causal causal algorithms Benefits • Competitive salary and equity options • Comprehensive health, dental, and vision insurance • Flexible working hours and remote work options • Professional development opportunities • A dynamic and supportive team environment