Role Description
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Perform exploratory data analysis and provide various insights into customer data using domain knowledge that would bring more value to the business.
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Leverage predictive analytics and AI/ML techniques to generate actionable insights for customer behavior, operational trends, and churn management.
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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.
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Build data ingesting pipelines and maintain them in big data ecosystems.
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Correlate analysis with real-time data from the customer database using churn data.
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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.
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Create solutions by comparing various Machine Learning algorithms that would best fit for the customer churn and use cases.
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Build the Machine Learning models in tools such as RapidMiner application to predict customer churn using Python scripts.
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Use algorithmic and logical approach to determine initial set of potential ML models based on the data and results generated.
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Maintain and suggest tools and technologies for increased productivity.
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Build and update business intelligence reports, databases, and dashboards to provide users with detailed intelligence.
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Architect end-to-end Machine Learning Model Deployment and Data Versioning pipeline in a production environment to identify data patterns and trends.
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Participate in model and algorithm deployment into production, which needs a separate pipeline built with support for monitoring and alerting.
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Align code branches to be managed with the latest algorithms to be used for customer churn predictability.
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Assure adherence to business intelligence standards, methodologies, and practice.
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Maintain the project codes/model versions using GIT/SVN version controlling tools.
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Document all the project details and activities in the organization’s Confluence pages.
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Develop technical design documentation to ensure the accurate development of reporting solutions.
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Create status reports on a weekly and monthly basis with an accurate assessment of the deliverables.
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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.
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Attend project meetings and work on ad hoc project report requests.
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Triage requirement gathering, identify business value for scenarios by working with product owners, and optimize data-driven decision making.
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Utilize statistical concepts/methodologies to correlate inventory, network statistics, and trouble management systems.
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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.
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Telecommuting and working from home permitted from anywhere in the U.S.
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Travel and relocation possible to unanticipated client locations throughout the U.S.
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Domestic travel required approximately 10% of the time to various client sites.
Qualifications
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Bachelor’s degree or foreign equivalent in Computer Science, Data Sciences, or Information Systems.
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3 years of experience in the job offered or related occupations of Lead Engineer, Software Engineer, Application Developer, or equivalent.
Requirements
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3 years of experience with GenAI Technologies such as LLMs, Prompt Design, Prompt Engineering, LangChain, Hugging Face.
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3 years with AI/ML Technologies such as Scikit-learn, TensorFlow, PyTorch, Keras, Pandas, NumPy, Spark ML, NLTK, H2O, AutoML, RapidMiner, Rasa, cuDNN.
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3 years of experience with Statistical Modelling & ML Algorithms such as Regression, Time Series Analysis, Random Forests, Gradient Boosting, K-Means, KNN, Neural Networks.
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3 years of experience with Model Evaluation & Testing such as Accuracy, Precision, Recall, Cross-Validation, A/B Testing, Hypothesis Testing.
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3 years of experience with MLOps & Deployment such as Docker, Kubernetes (AKS), CI/CD, Model Monitoring, Data Versioning.
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3 years of experience with API & Backend Development such as REST APIs, FastAPI, Uvicorn.
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3 years of experience with Data Engineering & Orchestration such as Apache Airflow, Kafka, Flume, Hadoop, Drill.
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3 years with Data Visualization & BI Tools such as Matplotlib, Seaborn, Grafana, Power BI, Tableau, Superset.
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3 years with Databases & Data Warehouses such as Snowflake, PostgreSQL, Oracle, MySQL, HBase, Hive, SQL.
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3 years with Cloud Technologies such as Azure (OpenAI, AI Search, ML), AWS (S3, Athena), GCP (Dialog flow, Data Studio).
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3 years with DevOps & Collaboration Tools such as Git, Jira, Confluence, Azure DevOps.
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3 years with Operating Systems such as Windows, Linux.
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Travel and relocation possible to unanticipated client locations throughout the U.S.
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Domestic travel required approximately 10% of the time to various client sites.
