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Synthesizes mechanical data across regions, enriches datasets, and creates working models that support regional and facility segmentation. Analyzes mechanical department processes and reporting to design regional and facility-specific Key Performance Indicators and metrics that highlight performance and productivity. Curates datasets from multiple sources, cleaning, normalizing, scaling, and imputing while deriving features for modelling. Supports advanced analysis and modelling efforts for the customer analytics team. Collaborates with IT and business partners to onboard new data sources, perform profiling and scoring, and track data quality. Develops programmatic visualizations to communicate findings with executive leadership. Leverages machine learning and natural language processing techniques to data mine customer feedback and provide proactive reporting to senior leadership.
Job Responsibility
Synthesizes mechanical data across regions, enriches datasets, and creates working models that support regional and facility segmentation
Analyzes mechanical department processes and reporting to design regional and facility-specific Key Performance Indicators and metrics that highlight performance and productivity
Curates datasets from multiple sources, cleaning, normalizing, scaling, and imputing while deriving features for modelling
Supports advanced analysis and modelling efforts for the customer analytics team
Collaborates with IT and business partners to onboard new data sources, perform profiling and scoring, and track data quality
Develops programmatic visualizations to communicate findings with executive leadership
Leverages machine learning and natural language processing techniques to data mine customer feedback and provide proactive reporting to senior leadership
Requirements
Bachelor's degree or equivalent in Computer Science, Data Science, Statistics, Engineering, or a related field and three (3) years of progressive, post-baccalaureate experience as a Lead Data Scientist Tableau or any occupation related to Data Science. Must also have three (3) years of experience: (1) Conducting exploratory data analysis for customer segmentation
(2) Using Python/R and SQL to program large scale data sets for customer-related data domains
(3) Cleaning, conforming, and summarizing data using imputation techniques and advanced feature engineering methods
(4) Troubleshooting, debugging, and interpreting codes
(5) Building reusable code including packages, libraries and stored procedures
(6) Extracting, processing, and analyzing unstructured data sources
(7) Utilizing visualization tools such as Business Objects, Tableau, or ggplot
(8) Applying data warehousing concepts including data integration, normalization, and optimization.