Description
We’re seeking an AI/ML Engineer with strong machine learning and Business Intelligence (BI) capabilities to accelerate data-driven decision making across our Fiber-to-the-Premises (FTTP) business. This role blends model development, analytics, and data storytelling to improve customer experience, network performance, and operational efficiency.
What You’ll Do
- Build, train, fine-tune, and deploy ML models for churn prediction, demand forecasting, network optimization, and service-risk scoring.
- Perform model validation, feature engineering, and performance monitoring to ensure accuracy and scalability.
- Develop scalable data pipelines and collaborate with data engineering to maintain data quality across BSS/OSS systems.
- Analyze FTTP data across construction, activation, utilization, service quality, and support processes.
- Design BI dashboards and reports that track critical KPIs for network, operations, CX, and finance using Tableau, Power BI, Looker, or open-source equivalents.
- Present insights through clear, structured data storytelling for technical and business stakeholders.
- Maintain documentation, code quality, and best practices in ML Ops, CI/CD, and version control workflows.
What You Bring
- Master’s degree (or equivalent experience) in Computer Science or related field, with 4+ years of progressive, hands-on experience.
- Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch, MLflow); R is a plus.
- Solid ML fundamentals including regression, classification, clustering, and time-series forecasting.
- Advanced SQL skills and experience working with large, complex datasets.
- Hands-on BI experience with modern visualization tools and strong data storytelling ability.
- Experience with AWS.
- Comfortable working in a dynamic, fast-paced start-up culture.
- Familiarity with LLMs and generative AI concepts.
- Knowledge of FTTP/telecom datasets (ONT/OLT telemetry, provisioning, work orders, inventory, Fieldops) is a plus.
- Proficiency with Git, CI/CD pipelines, and ML Ops practices.
Nice to Have
- Exposure to network performance analytics, geospatial (GIS) data, or streaming data pipelines.
- Knowledge of Precisely, Sitetracker, FCC(BDC) data sets.
- Experience with modern data warehouse environments (BigQuery, Snowflake, or open-source equivalents like ClickHouse, Trino, Iceberg).
- Background in telecom, broadband, utilities, or other data-rich operational domains.
Tags & focus areas
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