Python Developer - Machine Learning

Role Overview:

You will be responsible for Python development, data science, analytics, SQL & data engineering, cloud & DevOps, collaboration, and stakeholder engagement in this role. Your tasks will include developing data processing scripts, machine learning model pipelines, applying data science techniques, writing complex SQL queries, working on cloud platforms, collaborating with cross-functional teams, and presenting technical solutions.

Key Responsibilities:

• Develop robust and efficient data processing scripts, automation tools, and backend components using Python.
• Build and maintain machine learning model pipelines, reusable modules, and data utilities.
• Integrate Python applications with databases, APIs, and cloud services.
• Optimize code for performance, scalability, and readability.
• Apply data science techniques to analyze datasets, derive insights, and support business decision-making.
• Implement statistical methods, predictive models, and data transformations.
• Collaborate with Data Scientists to deploy models into production environments.
• Conduct exploratory data analysis (EDA), data cleaning, and feature engineering.
• Write complex SQL queries to extract, transform, and analyze data from relational databases.
• Work with large datasets and contribute to designing efficient data structures.
• Collaborate with data engineers to improve data pipelines and workflows.
• Work on cloud platforms including Azure, AWS, or GCP for data and compute workloads.
• Utilize DevOps tools for CI/CD, version control, and automated deployments. Work with containerization technologies such as Docker.
• Assist in setting up and managing cloud-based data environments and monitoring processes.
• Collaborate with Business Units (BU), vendors, and cross-functional teams to understand requirements.
• Translate business problems into technical solutions using data-driven approaches.
• Present results, findings, and technical solutions in a clear and concise manner.
• Participate in Agile ceremonies like sprint planning, retrospectives, and reviews.

Qualification Required:

• Minimum 4+ years of strong programming experience with Python, including libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, etc.
• Minimum 2+ years of hands-on data science experience including EDA, ML models, and data wrangling.
• Minimum 2+ years of experience writing efficient SQL queries.
• Hands-on experience with any cloud service provider (Azure preferred, AWS, or GCP).
• Experience with Git, CI/CD pipelines, version control, and automation tools.

Please note that the company did not provide any additional details in the job description. Role Overview:

You will be responsible for Python development, data science, analytics, SQL & data engineering, cloud & DevOps, collaboration, and stakeholder engagement in this role. Your tasks will include developing data processing scripts, machine learning model pipelines, applying data science techniques, writing complex SQL queries, working on cloud platforms, collaborating with cross-functional teams, and presenting technical solutions.

Key Responsibilities:

• Develop robust and efficient data processing scripts, automation tools, and backend components using Python.
• Build and maintain machine learning model pipelines, reusable modules, and data utilities.
• Integrate Python applications with databases, APIs, and cloud services.
• Optimize code for performance, scalability, and readability.
• Apply data science techniques to analyze datasets, derive insights, and support business decision-making.
• Implement statistical methods, predictive models, and data transformations.
• Collaborate with Data Scientists to deploy models into production environments.
• Conduct exploratory data analysis (EDA), data cleaning, and feature engineering.
• Write complex SQL queries to extract, transform, and analyze data from relational databases.
• Work with large datasets and contribute to designing efficient data structures.
• Collaborate with data engineers to improve data pipelines and workflows.
• Work on cloud platforms including Azure, AWS, or GCP for data and compute workloads.
• Utilize DevOps tools for CI/CD, version control, and automated deployments. Work with containerization technologies such as Docker.
• Assist in setting up and managing cloud-based data environments and monitoring processes.
• Collaborate with Business Units (BU), vendors, and cross-functional teams to understand requirements.
• Translate business problems into technical solutions using data-driven approaches.
• Present results, findings, and technical solutions in a clear and concise manner.
• Participate in Agile ceremonies like sprint planning, retrospectives, and reviews.

Qualification Required:

• Minimum 4+ years of strong programming experience with Python, including libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, etc.
• Minimum 2+ years of hands-on data science experience including EDA, ML mode