Summary

At Moelis & Company, we share an entrepreneurial mindset and collaborate to develop data-driven actionable intelligence. 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 to shape our future firm.

You’ll join a fast growing team that will have high impact as we develop solutions that create value for our clients and our people. This entrepreneurial data science and machine learning Intern role involves working closely with our data 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 enthusiasm for solving complex problems.

We are seeking an Intern team member, who will be responsible for analyzing data and developing 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 drive enhanced business decision-making. They will also be comfortable interpreting and explaining the findings of analyses as it applies to the business problem in simple terms.

Responsibilities

Work with stakeholders, 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.

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

Provide technical excellence to apply state-of-the-art machine intelligence 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 and deep 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.

Required Skills and Experience

• Entrepreneurial mindset
• Must be enrolled in an Undergraduate, Master’s or PhD degree program in data science, math, statistics, sciences, engineering, computer science or other quantitative or computing field
• Expertise querying Relational / No-SQL databases and using statistical programming languages such as Python and/or R is required
• Excellent analytical, quantitative and critical problem solving skills and demonstrated research ability
• Knowledge of machine learning / data science theory, techniques and tools; experience with Natural Language Processing (NLP) a plus
• Strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience

Additionally preferred skills, though not required: 

• An understanding of finance and financial analysis
• Experience with R-Shiny, Python-Dash, or web-scraping
• Experience with big-data technologies such as Spark, SparkML, Sagemaker, etc.
• Knowledge in Reinforcement Learning or Meta Learning