Data Science Analyst, Information Technology - New York

We are passionate about our business and our culture, and are seeking individuals with that same drive.

Summary

At Moelis & Company, we collaborate to develop data-driven actionable intelligence that serves internal teams and external clients. We’re focused on innovating and creatively solving for business opportunities. We’re looking for fresh perspectives and top creative, analytical minds to harness the power of data assets across our Businesses.

You’ll join a team of problem-solvers who develop impactful solutions that create value for our clients and our people. This data science role involves working closely within our Data Science & Analytics team, cross-industry businesses, and technologists to develop and deliver insights with the greatest business impact. The successful incoming candidate will have a passion for technology, be comfortable working across a range of technology capabilities, and have enthusiasm for solving complex problems.

We are seeking an Analyst who will be responsible for analyzing data and assist with the development of models for business-driven use cases across our Firm. The successful candidate will bring an innovative, analytical perspective to the team and be able to apply machine learning to data assets to enhance business decision-making. They will be able to recognize which statistical methods are suitable for the business problem at hand and be comfortable explaining their findings in simple terms.

Responsibilities

• Work with stakeholders as an internal consultant, identifying opportunities for leveraging data to solve for business challenges and opportunities. Partner with business and technology teams across the organization to evolve data science and machine learning capabilities.

• Develop thoughtful analyses and predictive models responsive to project requirements.

• Engage in end-to-end data science projects from data curation to fitting models to productionizing at scale.

• Apply technical knowledge of corporate finance, statistics, and programing to real world business problems. Define strategies and parameters for predictive models and data mining projects, ensuring data integrity and usability.

• Combine machine learning techniques with unique data assets to optimize business decisions. Develop tools to leverage machine learning models to solve business use cases.

• Research and implement custom statistical models and machine learning algorithms. Develop models using cutting-edge tools and machine learning techniques.

• Identify valuable data sources / datasets that can be leveraged to improve results.

Required Skills and Experience

• 1 year of work-experience, preferably in Banking, Consulting, or similar environments

• Undergraduate or Master’s degree in data science, math, statistics, quantitative / computational finance, engineering, computer science or other quantitative / computing field.

• Expertise using programming languages such as Python to run analyses and SQL for querying relational databases.

• Excellent analytical, quantitative and critical problem-solving skills and demonstrated research ability.

• Demonstrated ability to adapt quickly and deliver high-quality results under tight timelines despite competing demands.

• A strong interest or previous experience in corporate finance or investment banking

• Knowledge of machine learning / data science theory, techniques and tools; experience with Natural Language Processing (NLP) is a plus.

• Understanding of Large Language Model capabilities and underlying structures.

• Interest in application of emerging technologies such as AI.

• Strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience.

• Additional preferred skills (though not required):

Additional Preferred Skills (Not Required Skills)

• Experience with data visualizations (e.g. Python-Dash, R-Shiny, Tableau, etc.).

Expected Salary: USD $90,000

We are an Equal Opportunity Employer. Applicants are considered for employment opportunities without regard to race, age, religion, color, sex (including pregnancy), national origin, marital status, veteran status, sexual orientation, political affiliation, citizenship status, genetic information, disability (in compliance with the Americans with Disabilities Act and any other applicable law), or any other characteristic or status protected under any applicable US, state or other law.