Job Overview:Designing, developing, and maintaining scalable backend systems, APIs, and applications that transform data science and analytics outputs into reliable production solutions and works closely with data scientists, data engineers, and analysts to produce machine learning models, analytics workflows, and data-driven insights into internal tools and client-facing products.Job Responsibilities:Design and develop scalable backend services and APIs that support data-driven products and analytics platforms to enable seamless access to data, analytics, and machine learning capabilities through reliable and scalable system interfaces.Build robust systems that enable the integration of analytics workflows and machine learning models into applications to ensure that analytical insights and predictive models can be effectively utilized within operational business applications.Develop integrations with relational databases, APIs, and external systems to allow efficient data exchange and connectivity between internal platforms and external services.Ensure high system performance, reliability, and scalability of services to maintain stable and efficient system operations that support growing data and user demands. Collaborate with data scientists and data engineers to deploy and operationalize machine learning models and analytics pipelines to transition analytical models from experimentation into production-ready solutions that deliver business value.Build applications and services that expose data insights, analytics outputs, and machine learning predictions to users and other systems to make data-driven insights accessible and actionable for both internal stakeholders and external clients.Develop internal tools and client-facing solutions that interact with data platforms and services to enhance operational efficiency and provide user-friendly access to data capabilities.Containerize applications and manage deployments using modern DevOps practices to ensure consistent, scalable, and efficient application deployment across environments.Maintain CI/CD pipelines and ensure efficient software delivery process to enable continuous integration and deployment, improving development speed and software quality.Implement logging, monitoring, and alerting mechanisms to maintain system reliability to detect, diagnose, and resolve system issues quickly while maintaining service stability.Support production environments and troubleshoot system issues when required to ensure minimal system downtime and maintain smooth operational performance.Contribute to the design and architecture of scalable, production-grade systems to build reliable and maintainable software systems capable of supporting complex data products.Optimize system performance, API response times, and database queries to enhance system efficiency and provide fast, responsive services to users and applications.Ensure security and best practices in system development and deployment to protect data, systems, and infrastructure from vulnerabilities and security risks.Provide technical guidance and mentorship to junior engineers when needed to support team development, improve technical skills, and maintain engineering excellence.Contribute to improving engineering standards, development processes, and code quality to maintain high-quality software development practices and ensure long-term system sustainability.Job Qualifications:Bachelor’s degree in actuarial science, Mathematics, Statistics, Computer Science, Computer Engineering, or Business Informatics.Minimum 3+ years of experience in software engineering or backend development.Experience building and maintaining production-grade systems and APIs.Experience working with data-driven applications or analytics platforms is preferred.Strong programming experience in Python.Experience developing RESTful APIs and backend services.Strong knowledge of relational databases such as PostgreSQL or similar.Experience with Docker and containerized application deployment.Understanding of system scalability, performance optimization, and reliability.Experience working with version control systems (Git) and collaborative development workflows.Experience working with cloud platforms (AWS, GCP, or Azure).Experience with React for frontend development.Familiarity with TypeScript or modern JavaScript frameworks.Experience integrating frontend applications with backend APIs.Experience with Kubernetes or container orchestration platforms.Experience deploying machine learning models into production environments.Familiarity with data pipelines, ETL processes, or analytics platforms