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Senior Data Scientist

Ameren


Location:
St. Louis, Missouri 63103
Date:
09/12/2017
2017-09-122017-10-12
Job Type:
Employee
Job Status:
Full Time
Ameren
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Job Details

The Senior Data Scientist has the opportunity to shape the future of the organization's approach to using and consuming data and drive processes for extracting insights from that data in new and creative ways. The Senior Data Scientist is responsible for contributing, both individually and as a part of a team, to design and implement complex processes related to predictive/analytical modeling, data mining and research on large scale complex data sets. This position uses statistical analysis, graph modeling, text mining and other analytical techniques from initial data collection and conditioning to draw conclusions and results.  May adapt procedures, processes, and techniques to meet the more complex requirements of this position. This position plans, leads and collaborates with various internal and vendor teams, manages the lifecycle of analysis projects, and provides periodic updates to stakeholders and executive leadership through presentations and prototype demonstrations.


Key responsibilities include:

  • Create valuable, transformative business strategies through the measurement, manipulation, reporting, and dissemination of broad sets of data.

  • Analyze large data sets using a variety of techniques from statistical modeling to machine learning algorithms.

  • Apply and advise on state-of-the-art, advanced analytic and quantitative values.

  • Develop and plan required analytic projects in response to business needs.

  • Execute analytical projects as an individual contributor.

  • Develop new predictive/analytical modeling methods as required.

  • Work with the Data Strategist to identify data relevant for analysis.

  • Create data definitions for new database file/table development and/or changes to existing ones as needed for analysis.

  • In conjunction with data owners and department managers, contribute to the development of data models for analytics.

  • Contribute to predictive/analytical modeling architectures, modeling standards, reporting, and data analysis methodologies.

  • Contribute to recommendations on predictive/analytical modeling products, services, protocols, and standards in support of business processes.

  • Collaborate with unit managers, end users, development staff, and other stakeholders to enhance operations by supplying data analytics insights into business processes.

  • Apply quality assurance best practices for predictive modeling/analytics services. 

  • Adhere to change control and testing processes for modifications to analytical models.

  • Collaborate and leverage the skills within the Data Analytics team to achieve desired results and increase adoption of analytics across the enterprise.

  • Stay abreast of trends in forecasting including methodologies and data availability.

  • Research mathematical models, methods, and best practices for data architecture and develop practical tools based on research findings.

  • Present results of analysis work to business stakeholders, explaining the conclusions of the analysis process in both written and oral presentation formats.

Requirements

Advanced degree in a technical discipline (e.g., engineering, mathematics, statistics, finance/economics, business management, or related field) with five or more years of related work experience required. Bachelor's Degree in a technical discipline (e.g., computer science, engineering, mathematics, statistics, economics or related field) with ten or more years of related work experience contributing individually or as part of a team to manage data analytics projects will be considered. Demonstrated work experience in statistics, programming and predictive modeling (such as linear and logistic regression) and machine learning algorithms (such as decision trees and artificial neural networks) is required. Demonstrated working knowledge of code writing required. Utility industry experience preferred.

 

In addition to the above qualifications, the successful candidate will demonstrate:


  • Strong critical thinking skills and ability to relate them to the products or services the company is producing.

  • Excellent knowledge (ability to write queries and code) of data mining and predictive modeling tools such as R, Python, SQL, AWS, SAS, SPSS, etc.

  • Ability to create compelling visualizations in software such as SAS Visual Analytics, Tableau, or Microsoft Power BI.

  • Strong understanding of predictive/analytical modeling techniques, theories, principles, and practices.

  • Data mining knowledge that spans a range of disciplines

  • Ability to conduct research into predictive/analytical modeling issues, practices, and products as required.

  • Strong familiarity and experience with data preparation and processing – such as assessment of data quality, new variable creation, variable selection, etc.

  • Proficient in assessing data needs for specifics analysis projects.

  • Ability to interpret the results of analytical work, assess its relevance to real world business results, and effectively communicate the information in plain language that is readily understood by business line leaders.

  • Proficient in working on multiple projects simultaneously, often with tight deadlines.

  • Strong intrinsic problem-solving skills, ability to structure and solve problems, and conduct and interpret analysis independently with demonstrated analytic and quantitative skills.

  • Strong listening and communication skills; ability to take direction; ability to bridge gap between data science and business management.

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