Senior Software Engineer

Role & responsibilities

1.Problem Solving & Troubleshooting:

•Analyse and resolve complex technical issues in production and development environments.

•Identify root causes of problems and design scalable, efficient solutions.

2.Data Science & Predictions:

•Develop predictive models to derive insights and support decision-making.

•Process, analyse, and visualize large datasets to extract actionable intelligence.

•Work on improving the systems ability to forecast trends and optimize outcomes.

3.Feature Design & Delivery:

•Independently design, implement, and deliver features that align with product goals.

•Collaborate with cross-functional teams to ensure seamless integration of data science components into the product. 4.Technical Expertise:

•Develop robust solutions using Python as the primary programming language.

•Implement and optimize machine learning models for real-time and batch predictions.

•Integrate with RESTful APIs and work with message queues (e.g., RabbitMQ, Redis) for data processing.

5.Cloud & Scalability:

•Design and deploy scalable, cloud-based solutions for predictive analytics.

•Optimize resource utilization and ensure system reliability on cloud platforms like AWS or GCP.

Key Qualifications:

•Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

•3+ years of experience in software engineering with a focus on data science and predictive analytics.

•Strong programming skills in Python.

•Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

•Solid understanding of RESTful services and message queue systems (e.g., RabbitMQ, Redis).

•Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker.

•Excellent debugging, problem-solving, and analytical skills.

•Ability to work independently and take ownership of complex tasks. Key Performance Indicators (KPIs):

•Successful implementation of predictive models that enhance system capabilities.

•Timely resolution of technical issues with minimal impact on production.

•Delivery of high-quality, scalable features within defined timelines. •Positive feedback from stakeholders on collaboration and technical contributions.

Preferred Skills:

•Experience with big data tools like Apache Spark or Hadoop. •Familiarity with monitoring tools (e.g., CloudWatch, Grafana). •Knowledge of CI/CD pipelines and DevOps practices.