Data Scientist - Finance AI & Analytics

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist - Finance AI & Analytics based in United States. This is an opportunity to join a high-impact Finance AI & Analytics team focused on turning complex business data into actionable insights. You will develop advanced statistical and machine learning models that help business leaders understand uncertainty and evaluate future scenarios. The role combines hands-on data science, modeling and simulation with strategic business problem-solving at enterprise scale. You will collaborate closely with data scientists, engineers, technology teams, and business stakeholders across a complex organization. Your work will directly support better planning, decision-making, and business management through data-driven analysis. The environment values intellectual curiosity, technical rigor, ethical thinking, and practical innovation. This role can be hired at either Level 3 or Level 4, depending on your education and professional experience, with a fully remote option available. Develop statistical and machine learning models using a modeling and simulation approach to quantify uncertainty, evaluate potential outcomes, and support business scenario planning. Translate complex finance and business-management challenges into well-defined analytical questions and determine the most appropriate methodologies to address them. Build clean, well-structured, understandable, and maintainable code that supports collaboration, reproducibility, and successful model deployment. Serve as a trusted technical advisor on data science methodologies, modeling approaches, and technology decisions, while communicating requirements effectively to technology partners. Work collaboratively across multiple teams to deliver analytics initiatives, manage stakeholder relationships, and communicate findings in a clear and actionable way. Mentor junior data science team members by sharing technical guidance, best practices, and approaches to solving complex analytical problems. Stay current with emerging data science, machine learning, and analytics methodologies and identify innovative opportunities to create measurable business value. Contribute to enterprise-level analytics transformation by helping evolve processes, technical capabilities, and data-driven decision-making practices. Requirements: Bachelor’s degree with 5+ years of related professional experience, Master’s degree with 3+ years, or PhD with 1+ years for Level 3; alternatively, Bachelor’s degree with 8+ years, Master’s degree with 6+ years, or PhD with 3+ years for Level 4. Deep foundational knowledge of statistical modeling and machine learning concepts, with the ability to select and apply appropriate techniques to complex business problems. At least 4 years of professional experience with Python and strong proficiency in data transformation using SQL or a comparable data-querying language. Experience using version control systems such as Git within collaborative development environments. Hands-on experience with cloud-based data science technologies such as AWS, Azure, Databricks, Spark, or PySpark. Proven ability to translate business challenges into analytical questions, develop data-driven solutions, and communicate findings to both technical and non-technical audiences. Strong collaboration and stakeholder-management skills, with the ability to work effectively across multiple teams and manage relationships throughout complex projects. A degree in a quantitative discipline such as computer science, mathematics, statistics, engineering, or a related field is preferred. Experience with Monte Carlo simulation, time-series modeling, probabilistic modeling, productionizing models, executive presentations, or finance/business-management data is highly desirable. U.S. citizenship may be required for positions involving government clearance or other restricted work.