Machine Learning Engineer

Company: Cerberus Capital Management
Location: New York, New York, United States
Type: Full-time
Posted: 03.SEP.2021
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Summary

As a machine learning engineer in our Data Science team, you will contribute to the firm's objectives by designing, implementing and deployi...

Description

As a machine learning engineer in our Data Science team, you will contribute to the firm's objectives by designing, implementing and deploying quantitative models for a broad range of business objectives, such as asset pricing, demand forecasting, sentiment analysis, and other machine-learning techniques for pattern recognition and statistical modeling. You may also participate in due diligence analyses of future investments, or evaluate 3rd party solutions and cloud-based tools for client adoption.

Responsibilities:

  • Develop and productionalize containerized algos for deployment in hybrid cloud environments (GCP, Azure)
  • Connect and blend data from various data sources within enterprise tools (python, pandas, or SQL) to enable application of Data Science methods
  • Create metrics and analytical reports to ensure data quality and business value. Clean, structure and normalize data to eliminate redundant or unnecessary information to enable robust and sound analysis
  • Participate in the development of both back-end data pipelines and front-end applications
  • Generate analytical reports to track adherence of client processes to business strategy
  • Apply statistical methods to predict future client business outcomes
  • Participate in due diligence of investment proposals as a Data Science and Technology expert
  • Evaluate 3rd party solutions for functionality, quality and applicability to client use cases.
Requirements:
  • University degree in Mathematics, Engineering, Statistics, Computer Science or Physics. Advanced degree preferred but not required.
  • Solid knowledge of Linear Algebra, Probability Theory, Statistics and Optimization, including regression analysis, parameter estimation, factors selection, PCA, hypothesis testing, time series, queuing theory, survival analysis, clustering, linear programming.
  • Knowledge of machine learning methods, such as regularization, random forests, neural networks and deep learning.
  • Ability to write algorithms and implement pipelines in Python. Knowledge of Scala, R, is a plus.
  • Experienced in SQL. Familiarity with various relational database platforms is a plus (SQL Server, MySql, PostgreSQL, Oracle, Snowflake, Vertica, etc). Ability to write efficient and robust queries.
  • Familiarity with DevOps process for model deployment and unit testing.
  • Experience of work in cloud environments, especially MS Azure, is a plus.
  • Experience of work in collaborative development environment (GIT, Azure DevOps, JIRA).
  • Ability to present ideas and solutions in business-friendly and user-friendly language to colleagues, management and clients.
Cerberus Capital Management (CCM) is a private equity firm with partial or full ownership stakes in over 40 companies in a variety of industries. Cerberus Technology Solutions (CTS) is a subsidiary of CCM that specializes in information organization, storage and analysis. The CTS teams include Data Science, Data Management and Client Engagement, which work closely together with clients to identify business opportunities and create new business value through improved data handling and analysis.

 
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