Come join us in reshaping the future!

As an Applied AI ML Senior Associate, in our Chief Modeling organization, you will work in the Chief Modeler’s team on developing cutting-edge models and techniques in the Marketing, Finance, and Operations domains.

Job Responsibilities

• Apply critical thinking skills and perform advanced statistical and mathematical analytics with the goal of solving complex and multi-faceted business problems.
• Generate deep insights through the analysis of data and understanding of business processes and turn them into actionable recommendations.
• Contribute to the full modeling lifecycle, including defining the objective and key decision variables, choosing and designing appropriate methodologies, developing and implementing efficient and scalable model suite, building insightful and explainable statistical tests to evaluate and monitor model performance. 
• Act as a subject matter expert and trusted advisor in the statistical, optimization and/or machine learning modeling discipline.
• Collaborate across teams of various functions, communicate and present analytics and modeling insights to both technical and non-technical audiences.
• Contribute to the continuous learning mindset of the organization by both bringing in and learning new knowledge, ideas, and perspectives.

Required qualifications, capabilities, and skills:

• Advanced degree in Statistics, Data Science, Engineering, Computer Science, Economics, Operations Research, Mathematics or an equivalent quantitative field
• Outstanding written and oral communication skills to present analytical findings and exercise influence among key project stakeholders.
• Experience in developing machine learning, optimization, and/or statistical models to solve real world problems (e.g. Classification, Regression, or Recommender Systems).
• Proficiency in SQL and at least one other programming language is required, such as Python.
• Strong analytical, interpretive, and problem-solving skills, with demonstrated ability of thinking outside the box.

Preferred qualifications, capabilities, and skills:

• Ph.D. in relevant quantitative field with demonstrated area of expertise, decision-making ability, adaptability, and creativity.
• Familiarity with big-data environments (e.g. Hadoop, Spark).
• Background or experience in Banking & Financial Services.