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Machine Learning Engineer


This is a Part-time position in Greenville, SC posted May 16, 2022.

As a GIS focused machine learning engineer in our Data Science team, you will contribute to the firms objectives by designing, implementing, and deploying quantitative models for a broad range of business objectives when involving geographic information and their relationship to pricing using 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.

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.

Responsibilities: Build predictive models using machine-learning techniques that generate solutions using geographical data assets 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: Working knowledge of GIS software such as ESRI is preferred.

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.

Other Requirements: U.S work authorization
– We are unable to provide sponsorship by Jobble