Python Backend Developer - Time Series and Forecasting | 3+ YOE

Company Description Axionix Technologies is a global leader in providing digital transformation solutions, working closely with top technology companies to deliver impactful results. Guided by innovation, agility, and a commitment to purpose, Axionix partners with clients from initial design to final operations. With expertise across multiple domains, the company specializes in embedding cutting-edge technology into its clients’ workflows. Axionix also helps organizations build quality tech teams and outsource digital projects to drive growth.

: We are looking for a Python Backend Developer with strong experience in time series analysis, forecasting, and data-driven backend systems. You will design and build scalable backend services that power forecasting pipelines, analytics platforms, and intelligent decision systems used across the business.

: • Design, build, and maintain robust backend services using Python. • Develop APIs and microservices to serve time series forecasts and analytics results. • Build and productionize forecasting pipelines for large-scale time series data. • Implement data ingestion, preprocessing, feature engineering, and model serving workflows. • Integrate forecasting models into production systems with monitoring and retraining pipelines. • Optimize systems for performance, scalability, and reliability. • Work closely with data scientists, ML engineers, and product teams to deploy forecasting solutions. • Ensure high code quality, testing coverage, and documentation.

: Core Python: • Strong Python programming experience. • Experience with backend frameworks such as FastAPI / Flask / Django. • REST API design and microservices architecture. • Solid understanding of asynchronous programming and performance optimization. • Experience with SQL and NoSQL databases (PostgreSQL, MongoDB, Redis, etc.). Time Series and Forecasting • Hands-on experience with time series modeling and forecasting techniques. • Experience with libraries such as: • statsmodels • Prophet • scikit-learn • pandas / numpy • Understanding of ARIMA/SARIMA, exponential smoothing, regression-based forecasting, or ML-based forecasting. • Experience handling seasonality, trend decomposition, anomaly detection. Data Systems: • Experience working with large time series datasets. • Knowledge of data pipelines, ETL, and batch/stream processing. • Familiarity with message queues (Kafka/RabbitMQ) is a plus. • Experience with Docker and cloud platforms (AWS/GCP/Azure).