Applied Scientist

For our client, we are seeking a Applied Scientist to join the team of a leader in the Finance & Insurance space. This role will focus on building and evaluating machine learning and statistical solutions that improve how customer offers are designed and selected. You will partner closely with cross-functional stakeholders to translate research into practical, production-ready outcomes that support better decision-making and business performance. The work blends causal inference, experimentation, and applied modeling in a highly data-driven environment. Strong collaboration and the ability to turn complex analysis into clear recommendations will be essential. Location: Remote Compensation: $141,500 – $196,000 annually Responsibilities Develop causal machine-learning models to optimize customer offers Analyze complex data and design experiments for model evaluation Measure the impact of offer changes through rigorous statistical experiments Translate research findings into actionable recommendations Build production-ready models for offer selection Collaborate with cross-functional teams on strategy and implementation Qualifications Graduate degree in a quantitative field such as mathematics, statistics, or computer science 2+ years of experience in machine learning or statistical modeling Proficiency in causal inference methods and experimentation Expertise in applied statistics and experimental design Production-quality coding experience in Python Benefits Competitive compensation with bonuses and equity grants 401(k) with company match for retirement savings Employee stock purchase plan with discounts Comprehensive health coverage including medical, dental, and vision Paid family and parental leave for caregiving support Annual wellness and productivity allowances for personal development Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.