Will design and implement data flow pipelines with various transformations to identify machine types (e.g., combines, sugar cane extractors, turbines) from distributed data. Defining boundaries for telematics machine data (e.g., mean, standard deviation) and filtering out machines that fall outside these boundaries. Interpreting data, analyzing results using statistical techniques, and providing ongoing reports, KPIs, metrics, and dashboards related to alerts, diagnostic test codes (DTC), warranty, and the value of expert alerts for end users. Developing SQL scripts to set standard coding guidelines, with proper comments where necessary. Implementing databases, data collection systems, and data analytics strategies to optimize statistical efficiency and quality. Acquiring data from primary or secondary data sources and maintaining databases/systems. Filtering and cleaning data by analyzing results and observing key performance indicators (KPIs) to locate and correct code issues. Assigning issued IDs to machines for different rules along with metadata and HTML links. Visualizing results using Seaborn (Python) or ggplot (R) for readability and analysis. Ensuring the delivery, quality, and visual presentation of data meet standards using tools like Databricks, Machine Learning Models, and Tableau. Creating Tableau dashboards to visualize the number of rules developed and the number of machines triggered, and share analysis with decision-makers. Designing and establishing relationships between different data elements through joins (left, right, inner) and unions. Creating clusters and IAM roles in Databricks with AWS for cloud infrastructure. Defining cluster specifications based on rule requirements and available data for analysis. Implementing Spark streaming to report issues with machines in real-time (within seconds of data being read from the data warehouse). Building machine learning models (both linear and nonlinear) to predict events such as air filter plugging, oil filter restrictions, etc. Selecting features based on correlation factors and consider collinearity. Filtering important features using Lasso Regression and train models on billions of records using distributed machine learning techniques. Tune hyperparameters for maximum accuracy. Log and register machine learning models with Databricks. Analyze residual data in Tableau for further insights. Position requires up to 100% domestic travel. This position is for full-time, salaried (W-2), permanent employment. REQUIREMENTS: Master’s Degree or foreign equivalent in Information Technology, Data Science or a closely related field and one year of experience in the Software Industry Please reference Job Number 165148E when sending resumes. Please mail resumes to: HR, Beacon Hill Solutions Group, LLC, 20 Ashburton Place, 5th Floor, Boston, MA 02108. California residents: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. If you would like to complete our voluntary self-identification form, please click here or copy and paste the following link into an open window in your browser: https://bhsg.com/jobs/eeoc/ Completion of this form is voluntary and will not affect your opportunity for employment, or the terms or conditions of your employment. This form will be used for reporting purposes only and will be kept separate from all other records. Beacon Hill offers a robust benefit package including, but not limited to, medical, dental, vision, and federal and state leave programs as required by applicable agency regulations to those that meet eligibility.  Upon successfully being hired, details will be provided related to our benefit offerings.