Senior Data Scientist

Senior Data Scientist, Network Intelligence About the Opportunit yOur client is transforming how large-scale network infrastructure is monitored and optimized through advanced machine learning and predictive analytics. As they continue investing in AI-driven network intelligence, they are seeking a Senior Data Scientist to build production-grade machine learning models that proactively identify network issues, improve operational efficiency, and enhance customer experience across complex telecommunications infrastructure .This is an opportunity to work on high-impact, real-world machine learning problems at scale, leveraging modern data platforms and MLOps best practices while partnering closely with engineering and network operations teams . What You'll DoAs a Senior Data Scientist, you'll lead the development and deployment of machine learning solutions that help create self-monitoring and increasingly self-optimizing network infrastructur e. Key responsibilities inclu de:Design, develop, and deploy machine learning models for anomaly detection, predictive maintenance, capacity forecasting, and network performance optimizati on.Build scalable feature engineering pipelines using Python, PySpark, and Databric ks.Manage the end-to-end ML lifecycle using MLflow, including experiment tracking, model versioning, deployment, and retraini ng.Apply statistical modeling, time-series forecasting, anomaly detection, and predictive analytics techniques to large-scale telemetry and operational datase ts.Develop optimization and scoring models that prioritize network incidents, maintenance activities, and operational ri sk.Integrate ML models into production automation and observability pipelin es.Collaborate with Data Engineering teams to define feature datasets and ensure high-quality data pipelin es.Present technical findings and model performance to senior technical and business stakeholde rs.Mentor junior data scientists and help establish best practices across the te am. What We're Looking For7+ years of experience building and deploying production machine learning or data science soluti ons.Strong Python skills with experience using libraries such as pandas, scikit-learn, XGBoost, PyTorch, or TensorF low.Hands-on experience with Databricks, MLflow, Delta Lake, and modern MLOps workfl ows.Expertise in statistical modeling, anomaly detection, predictive analytics, and time-series forecast ing.Experience working with large-scale telemetry, event-driven, or streaming datas ets.Strong understanding of feature engineering and model lifecycle managem ent.Ability to communicate technical concepts clearly to both technical and non-technical stakehold ers.Experience mentoring engineers or data scientists is highly val ued. Nice to HaveTelecommunications, networking, or infrastructure analytics experi ence.Familiarity with network performance metrics such as throughput, latency, packet loss, RSRP, RSRQ, or SINR.Experience with reinforcement learning, simulation-based optimization, or advanced decisioning sys tems.Experience with Databricks Feature Store or similar feature management platf orms.Databricks Machine Learning certifica tion.Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related discip line. Technology Stack PythonP ySparkData bricks MLflowDelt a Lake pandasscikit -learnX GBoostPyTorch / Tens orFlow Why Thi s Role?Build production AI and machine learning solutions that directly impact large-scale critical infrastr ucture.Work with modern cloud and MLOps technologies on complex, high-volume data pr oblems.Influence technical direction while mentoring other data scie ntists.Partner with engineering, operations, and executive leadership to deliver measurable business impact.Join a collaborative team focused on solving challenging real-world problems using machine learning at scale.

Lead the development and deployment of production-grade machine learning models for anomaly detection and network performance optimization. Collaborate with engineering teams to build scalable feature pipelines and integrate ML models into production observability systems.

Requires over 7 years of experience in deploying production ML solutions with strong proficiency in Python and the Databricks ecosystem. Expertise in statistical modeling and handling large-scale telemetry datasets is essential.

Identified from the job description. Confirm important requirements above.

• Python
• PySpark
• Databricks
• MLflow
• Anomaly Detection
• Predictive Maintenance
• Time-Series Forecasting
• Statistical Modeling
• Feature Engineering
• MLOps
• PyTorch
• TensorFlow
• XGBoost
• Scikit-learn
• Delta Lake
• Network Intelligence

• Data & Analytics
• Technology
• Engineering
• Software
• Science & Research

Minimum education

Bachelor’s degree

Minimum experience

7+ years

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available