Business Intelligence Analyst

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.

• 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 increased productivity.
• Build and update business intelligence reports, databases, and dashboards to provide users with detailed intelligence.
• Architect end-to-end Machine Learning Model Deployment and Data Versioning pipeline in a production environment to identify data patterns and trends.
• Participate in model and algorithm deployment into production, which needs a separate pipeline built with support for monitoring and alerting.
• Align code branches to be managed with the latest algorithms to be used for customer churn predictability.
• Assure adherence to business intelligence standards, methodologies, and practice.
• Maintain the project codes/ model versions using GIT/SVN version controlling tools.
• Document all the project details and activities in the organization’s Confluence pages.
• Develop technical design documentation to ensure the accurate development of reporting solutions.
• Create status reports on a weekly and monthly basis with an accurate assessment of the deliverables.
• Work with the team on the various AI/ML technologies, and business intelligence systems and tools, perform tests, and work with project managers and team on project deliverables.
• Attend project meetings and work on ad hoc project report requests.
• Triage requirement gathering, identify business value for scenarios by working with product owners, and optimize data-driven decision making.
• Utilize statistical concepts/methodologies to correlate inventory, network statistics, and trouble management systems.
• Explore and integrate AI/ML and GenAI frameworks to enhance customer communications and operational insights, including IVR call analytics and AI-driven outage intelligence across digital and self-service channels.
• Telecommuting and working from home permitted from anywhere in the U.S.
• Travel and relocation possible to unanticipated client locations throughout the U.S.
• Domestic travel required approximately 10% of the time to various client sites.

• Bachelor’s degree or foreign equivalent in Computer Science, Data Sciences, or Information Systems and 3 years of experience in the job offered or 3 years of experience in the related occupations of Lead Engineer, Software Engineer, Application Developer, or equivalent.
• Prior experience must include 3 years of experience with GenAI Technologies such as LLMs, Prompt Design, Prompt Engineering, LangChain, Hugging Face;
• 3 years with AI/ML Technologies such as Scikit-learn, TensorFlow, PyTorch, Keras, Pandas, NumPy, Spark ML, NLTK, H2O, AutoML, RapidMiner, Rasa, cuDNN;
• 3 years of experience with Statistical Modelling & ML Algorithms such as Regression, Time Series Analysis, Random Forests, Gradient Boosting, K-Means, KNN, Neural Networks;
• 3 years of experience with Model Evaluation & Testing such as Accuracy, Precision, Recall, Cross-Validation, A/B Testing, Hypothesis Testing;
• 3 years of experience with MLOps & Deployment such as Docker, Kubernetes (AKS), CI/CD, Model Monitoring, Data Versioning;
• 3 years of experience with API & Backend Development such as REST APIs, FastAPI, Uvicorn;
• 3 years of experience with Data Engineering & Orchestration such as Apache Airflow, Kafka, Flume, Hadoop, Drill;
• 3 years with Data Visualization & BI Tools such as Matplotlib, Seaborn, Grafana, Power BI, Tableau, Superset;
• 3 years with Databases & Data Warehouses such as Snowflake, PostgreSQL, Oracle, MySQL, HBase, Hive, SQL;
• 3 years with Cloud Technologies such as Azure (OpenAI, AI Search, ML), AWS (S3, Athena), GCP (Dialog flow, Data Studio);
• 3 years with DevOps & Collaboration Tools such as Git, Jira, Confluence, Azure DevOps;
• 3 years with Operating Systems such as Windows, Linux.
• Travel and relocation possible to unanticipated client locations throughout the U.S.
• Domestic travel required approximately 10% of the time to various client sites.