Python Algorithmic Language Developer

As a Python Algorithmic Language Developer, you will play a crucial role in designing, implementing, and maintaining complex algorithmic solutions using Python. You will work closely with cross-functional teams to identify areas of improvement, develop new features, and optimize existing ones. Your primary responsibility will be to drive innovation and excellence in software development while ensuring scalability, reliability, and performance.
Responsibilities:
Design, develop, test, and deploy large-scale data processing pipelines using Python.
Collaborate with data scientists, engineers, and other stakeholders to understand business requirements and translate them into technical specifications.
Write clean, efficient, and well-documented code that adheres to industry standards and best practices.
Debug and troubleshoot issues in existing codebases, and implement fixes to improve overall system stability and performance.
Stay up-to-date with emerging technologies and advancements in the field of computer science, and apply this knowledge to enhance the company’s technology stack.
Participate in code reviews and contribute to the development of coding standards and guidelines.
Work with external partners and vendors to integrate third-party libraries and tools into the company’s systems.
Ensure that all solutions are aligned with security protocols and compliance regulations.
Provide technical guidance and mentorship to junior developers, and support career growth within the organization.
Communicate effectively with both technical and non-technical stakeholders to ensure that projects are delivered on time and meet expectations.

Requirements:
Bachelor’s degree in Computer Science, Mathematics, Statistics, or related fields.
At least 3 years of experience working as a Python developer or data scientist.
Proficient in Python programming language, including various libraries and frameworks such as NumPy, Pandas, scikit-learn, TensorFlow, Keras, PyTorch, Flask, Django, and SQL databases.
Experience with data engineering, data warehousing, ETL processes, and big data analytics.
Knowledge of cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
Familiarity with agile software development methodologies and version control systems like Git.
Excellent problem-solving skills, attention to detail, and ability to work independently or as part of a team.
Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Ability to learn quickly and adapt to changing priorities and technologies.
Passion for continuous learning and staying updated on latest technologies and trends in the field.
Nice to Have:
Master’s degree in Computer Science or related fields.
Experience with machine learning frameworks and deep learning libraries such as PyTorch, Keras, or TensorFlow.
Knowledge of graph theory, network analysis, or computational complexity theory.
Familiarity with DevOps tools such as Jenkins, Docker, or Ansible.
Experience with database management systems such as MySQL, PostgreSQL, or MongoDB.
Understanding of software testing principles and methodologies.
Familiarity with containerization technologies such as Kubernetes.
Experience with CI/CD tools such as Travis CI, CircleCI, or GitHub Actions.