Prodapt Solutions

Business Intelligence Analyst

Prodapt Solutions
US Portland, OR, US
Onsite 2026-06-16
Estimated salary · Portland
~ $66,010 - $91,637
Low
$88K
Median
$116K
High
$153K
Market in Portland · BLS OEWS 2025
Estimated net pay
$4,231 - $5,572
/month · 23% withheld
after tax & contributions · on the estimated salary · Single, no dependents

Job description

Overview: Prodapt is the largest specialized player in the Connectedness industry. As an AI\-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences of tomorrow. A ServiceNow\-invested company, Prodapt has been recognized by Gartner as a Large, Telecom\-Native, Regional IT Service Provider. A “Great Place To Work® Certified™” company, Prodapt employs over 6,000 technology and domain experts across the Americas, Europe, India, Africa, \& Japan. Prodapt is part of the 130\-year\-old business conglomerate The Jhaver Group, which employs over 32,000 people across 80\+ locations globally. Responsibilities: * Perform exploratory data analysis and provide various insights into customer data using domain knowledge that would bring more value to the business. * Leverage predictive analytics and AI/ML techniques to generate actionable insights for customer behavior, operational trends, and churn management. * Study key data from the customer, inventory, network and trouble management systems and provide recommendations on the solutions that can be built out of the provided dataset. * Build data ingesting pipelines and maintain them in big data ecosystems. * Correlate analysis with real\-time data from the customer database using churn data. * Design, build, test, and tune machine learning models using Python and other tools, focusing on accuracy and ensuring that intelligence is consistent with defined needs. * Create solutions by comparing various Machine Learning algorithms that would best fit for the customer churn and use cases. * Build the Machine Learning models in tools such as RapidMiner application to predict customer churn using Python scripts. * Use algorithmic and logical approach to determine initial set of potential ML models based on the data and results generated. * Maintain and suggest tools and technologies for incre

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