- Build predictive models using machine-learning techniques that generate data-driven insights on modern data platforms (Spark, Hadoop and other map-reduce tools);
- 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 Technology expert
- Evaluate 3rd party solutions for functionality, quality and applicability to client use cases.
- 6+ Years of experience in an engineering role with a degree in Mathematics, Engineering, Statistics, Computer Science or Physics. Advanced degree preferred but not required.
- 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.
- Experience with 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.
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Software Engineer, Machine Learning - London Area, United Kingdom - Cerberus Capital Management
Description
Machine Learning Engineer at Cerberus Capital Management
As a machine learning engineer on our CTS team, you will contribute to the firm's objectives by designing, implementing and deploying tools and solutions 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.
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:
Requirements:
About Us:
Established in 1992, Cerberus Capital Management, L.P., together with its affiliates, is one of the world's leading private investment firms. Through its team of investment and operations professionals, Cerberus specializes in providing both financial resources and operational expertise to help transform undervalued and underperforming companies into industry leaders for long-term success and value creation. Cerberus holds controlling or significant minority interests in companies around the world.
The Firm's proprietary operations team, Cerberus Operations and Advisory Company, LLC (COAC), employs world-class operating executives to support Cerberus' investment teams in the following areas: sourcing opportunities, conducting highly informed due diligence, taking interim management roles, monitoring the performance of investments and assisting in the planning and implementation of operational improvement initiatives at Cerberus' portfolio companies.
Cerberus Technology Solutions is an operating company and subsidiary of Cerberus Capital Management focused exclusively on leveraging emerging technology, data, and advanced analytics to drive transformations. Our expert technologists work closely with Cerberus investment and operating professionals across our global businesses and platforms on a variety of operating initiatives targeted at improving systems and generating value from data.
