Come join us in reshaping the future!
As an Applied AI ML Senior Associate, in our Business Modeling organization, you will work on developing cutting-edge models and techniques in the Marketing, Finance, and Operations domains.
Job Responsibilities
• Apply critical thinking skills and perform advanced 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 appropriate methodologies, performing advanced quantitative and statistical analysis of large datasets, and communicating results.
• Act as a subject matter expert and trusted advisor in the statistical, optimization and/or machine learning modeling discipline.
• Contribute to the continuous learning mindset of the organization by bringing in 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. is preferred
• Familiarity with big-data environments (e.g. Hadoop, Spark) and model development experience on a cloud development platform
• Banking & Financial Services background or experience.
Location: Columbus, OH
Posted: Sept. 19, 2024, 11:44 p.m.
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