Data Scientist--Reliability

Excel Talent Solutions

Data Scientist with 4+ years experience in industrial IoT predictive reliability solutions.

  • PhD in Data Science, Math, or related
  • Python [numpy, pandas, sklearn], Matlab, R
  • IoT solutions, predictive analytics and modeling
Our client is a global manufacturing and solutions integrator poised two double in size through strategic acquisitions and organic expansion. Supporting a key division contributing directly to increased revenue via market-leading predictive support and optimization solutions, this individual will lead the data science effort for the IIOT team. Critical deliverables include working with large data sets via a cloud-based data lake in the development and implementation of advanced machine learning algorithms for predictive analytical software solutions.

As a Reliability Data Scientist, you will be responsible for the analysis of complex data sets including but not limited to time series, static classifications, and failure events. Your analysis would include the design of novel algorithms and approaches to drawing important insights out of our varied data sources. Your work will require inputs from subject matter experts, direct customer experience, and product development leadership. The output of your analysis will be embedded into an industry leading product for predicting failure and optimizing maintenance for industrial assets.

You will be working with a dynamic and collaborative team that integrates a wide array of technologies into a cohesive software product and leaves a foot-print in the smart IoT products industry.

Essential functions include:
  • Cleaning, preprocessing, and verifying data from our various sources
  • Development of novel algorithms taking inputs from numerous data sources using skills in feature selection and statistical analysis for both regressions and classification systems
  • Interfacing with subject matter experts to account for their experiential understanding of the industry
  • Building high quality models to be integrated into our end product
  • Automation of model maintenance and performance tracking
  • Ensuring that implementation team understands the high level approaches by creating comprehensive documentation
What they are seeking:
  • PhD in Mathematics, Computational Engineering, or Data Science along with four or more years’ experience as a data scientist implementing models into production systems
  • Deep understanding of statistics and machine learning techniques / algorithms for regressions, forecasting, and classifications
  • Experience querying from SQL Databases
  • Experience with common data science tools and packages (Python [numpy, pandas, sklearn], Matlab, R) Experience with Python is a huge plus for integrating with product team
  • Experience with data visualization tools for presenting out finding (d3.js, Tableau, Excel)
  • Experience in Agile/Scrum work environments with associated tools (Jira, Confluence)